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22 posts from November 2011

November 16, 2011

Innovation and Corporate Culture

Annually, Booz & Company analysts issue a report about corporate innovation. This year's study focuses on corporate culture. ["The Global Innovation 1000: Why Culture Is Key," by Barry Jaruzelski, John Loehr, and Richard Holman, Strategy + Business, 25 October 2011]. The authors of the study write:

"The elements that make up a truly innovative company are many: a focused innovation strategy, a winning overall business strategy, deep customer insight, great talent, and the right set of capabilities to achieve successful execution. More important than any of the individual elements, however, is the role played by corporate culture — the organization's self-sustaining patterns of behaving, feeling, thinking, and believing — in tying them all together."

Despite singling out corporate culture as the most important trait of innovative companies, the study concludes that "only about half of all companies say their corporate culture robustly supports their innovation strategy. Moreover, about the same proportion say their innovation strategy is inadequately aligned with their overall corporate strategy." I wish I could write that I find those statements surprising; but, I can't. By its very nature, innovation has a tense relationship with industrial age organizations. Innovation focuses on change -- organizational structure focuses on stability. There is nothing inherently good or bad about this corporate tension. It's how executives deal with this tension that determines whether it is helpful or hurtful. The authors continue:

"This disconnect, as the saying goes, is both a problem and an opportunity. Our data shows that companies with unsupportive cultures and poor strategic alignment significantly underperform their competitors. Moreover, most executives understand what's at stake and what matters, even if their companies don't always seem to get it right."

They go on to point out that even though most company executives claim to have the customer's best interests in mind, only those that put words into action rise to the top of the heap of innovative companies. The authors continue:

"If more companies could gain traction in closing both the strategic alignment and culture gaps to better realize these goals and attributes, not only would their financial performance improve, but the data suggests that the potential gains might be large enough to improve the overall growth rate of the global economy."

The Booz & Company analysts aren't the first to assert that corporate alignment is critical to success and they won't be the last. The fact that so many analysts harp on it, and yet so many companies remain out of alignment, is evidence of how difficult true corporate alignment is to achieve. In past posts about corporate alignment and corporate silos, I've discussed many of the reasons that breaking down those silos is difficult -- corporate culture is certainly one reason. For example, many executives are rewarded for maximizing key performance indicators (KPIs) related to specifically and uniquely to their silos rather than being rewarded for helping to achieve overall company goals. When the KPIs of different departments conflict (say between operations and marketing), executives are in a win-lose situation and the company is in a lose-lose situation. When the corporate culture encourages cooperation and alignment, and rewards executives on overall business success rather than silo KPIs, everybody wins. Changing a corporate culture, however, is normally very difficult. The Booz & Company study looks specifically at corporate culture and its relationship with innovation. The authors continue:

"The ways R&D managers and corporate decision makers think about their new products and services — and how they feel about intangibles such as risk, creativity, openness, and collaboration — are critical for success. As part of this year’s study, we surveyed almost 600 innovation leaders in companies around the world, large and small, in every major industry sector. As noted, almost half of the companies reported inadequate strategic alignment and poor cultural support for their innovation strategies. Possibly even more surprising, nearly 20 percent of companies said they didn't have a well-defined innovation strategy at all."

When executives look at companies like Apple or 3M, i.e., companies that recognized year after year for their excellence and innovation, it is hard to imagine that some executives still don't appear to believe that having a strategy for innovation is important. The authors of the study call this an "alignment gap." They write:

"Issues of culture have long been of great concern to corporate executives and management theorists alike, whether they apply to companies as a whole or to selected areas such as innovation. The reason is obvious: Culture matters, enormously. Studies have shown again and again that there may be no more critical source of business success or failure than a company's culture — it trumps strategy and leadership. That isn't to say that strategy doesn't matter, but rather that the particular strategy a company employs will succeed only if it is supported by the appropriate cultural attributes. ... Not surprisingly, companies saddled with both poor alignment and poor cultural support perform at a much lower level than well-aligned companies. In fact, companies with both highly aligned cultures and highly aligned innovation strategies have 30 percent higher enterprise value growth and 17 percent higher profit growth than companies with low degrees of alignment. ... Companies whose strategic goals are clear, and whose cultures strongly support those goals, possess a huge advantage."

The poster child for corporate innovation offered up by Jaruzelski, Loehr, and Holman is 3M. They claim 3M is successful because it has no alignment gap. Writing about companies that do have a gap, they report:

"In general, companies ... continue to show a range of significant gaps in how their strategic goals and cultural attributes contribute to performance and support their innovation. Companies that underperform their peers have much to gain if they can close these gaps and achieve much higher degrees of cultural and strategic alignment. We believe the way to do so lies in gaining a greater understanding of the cultural attributes that any given company needs to foster, given its particular innovation strategy. Soma Somasundaram, executive vice president of the Fluid Management segment at the Dover Corporation, describes the challenge this way: 'Poor innovation performance is usually not caused by a lack of ideas or lack of aspirations. What some companies lack is the structure needed to effectively dedicate resources to innovation. It's the lack of will to develop a strategy that can balance today's need versus tomorrow's.'"

In a previous post, I noted that one reason that long-term objectives have fallen victim to short-term goals is the fact that many CEOs are finding it more difficult to keep their jobs for a significant length of time. Boards and shareholders are looking for quick fixes and short-term wins. To save their jobs, many executives are willing to sacrifice tomorrow's needs on the altar of expediency. As a result, corporate culture and innovation are victims caught in the crossfire. Jaruzelski, Loehr, and Holman identified three principal innovation strategies based on a company's "approach to incremental versus breakthrough innovation and the role that end customers play in defining future product needs." The first strategy, which they label "Need Seekers," is very customer oriented.

"• Need Seekers actively and directly engage both current and potential customers to help shape new products and services based on superior end-user understanding. These companies often address unarticulated needs and then work to be first to market with the resulting new products and services."

Perhaps the most important part of that description is the fact that Need Seekers attempt to "address unarticulated needs." Clayton Christensen, noted in his book The Innovator's Dilemma that one of the things that many businesses do wrong is to listen to their customers. By that he means that manufacturers give customers what they say they want without really understanding what they are trying to accomplish -- that is, without understanding their unarticulated needs. Although I agree with that part of the strategy, I have my doubts about the value of the second part of the strategy, i.e., trying to be the first to market. Often, it is a very bad strategy. For more on that topic, read my post entitled First to Market vs. Late to the Game. The second strategy, which the authors call "Market Readers," is more cautious.

"• Market Readers closely monitor both their customers and competitors, but they maintain a more cautious approach. They focus largely on creating value through incremental innovations to their products and being 'fast followers' in the marketplace."

In their book entitled Beyond the Familiar: Long-Term Growth Through Customer Focus And Innovation, Patrick Barwise and Seán Meehan argue "that the heroic strategic shifts, breakthrough products and transformational acquisitions that are the stuff of business legend offer a perilous path to success." ["No need for acts of management bravado," Review by Andrew Hill, Financial Times, 30 March 2011] Barwise and Meehan believe that incremental innovation is generally the best strategy to follow. However, they agree with Booz & Company analysts when it comes to the subject of culture. Hill writes that they present a "crushing case study of General Motors' 'dismal' record over the past half-century. The company 'has had a culture which rejects unwelcome news, and its leaders have been unable or unwilling to change this', they write. The opposite of a GM-style culture of 'fear and denial' is the 'open organisation'." The final strategy identified by Jaruzelski, Loehr, and Holman, which they call "Technology Drivers," is obviously more technology focused. They write:

"• Technology Drivers follow the direction suggested by their technological capabilities, leveraging their sustained investments in R&D to drive both breakthrough innovation and incremental change. They often seek to solve the unarticulated needs of their customers through leading-edge new technology."

They conclude: "Just as companies following any of these three strategies can succeed, so any company can manifest strong strategic and cultural alignment, no matter which strategy it follows. A closer look at the survey results, however, does suggest that companies perfecting one strategy — the Need Seekers — are relatively advantaged. They consistently demonstrate better achievement on a number of strategic and cultural variables. Additionally, Need Seekers are more likely to financially outperform their rivals than companies following one of the other two strategies." For anyone interested in this subject, I suggest reading the entire study. Barwise and Meehan agree with Jaruzelski, Loehr, and Holman that corporate culture is critical and the ideal culture is one "where problems and ideas are freely discussed, managers get honest feedback and minions' mistakes earn a pat on the back." Unlike Jaruzelski, Loehr, and Holman, however, Barwise and Meehan disagree about which strategy is best. On reason is that they believe that maintaining the ideal corporate culture is difficult "as long as executives remain open to the temptations of heroism." You be the judge.

November 15, 2011

Social Media and the Supply Chain

Today you'll notice that there is a new name, look, and feel to the blog. The change was made to complement Enterra Solutions' new web site. It seemed fitting to make the change on post discussing social media.

At a recent conference, Adrian Gonzalez asked the audience, "Is Social Media in Supply Chain Management a Waste of Time?" [Logistics Viewpoints, 12 October 2011] To demonstrate that he wasn't the only person wondering about the answer to that question, he showed the audience a Dilbert cartoon where, in the first panel, a co-worker has just asked Wally for some help. Wally replies, "I can't help you because I'm busy working on a social network strategy for our global supply chain." To which the co-worker replies, "That sounds like something that no one wants and no one needs." Nonplussed, Wally retorts, "That's probably why it's taking so long."

Frankly, a lot of companies are struggling to develop a relevant social media strategy. It's not easy because each company's situation is different. Each target audience is different. What social media has to offer various enterprises is idiosyncratic. Based on Gonzalez' question and his use of the Dilbert cartoon, you might conclude that he is anti-social media. You'd be wrong. He writes:

"Based on the huge turnout and the interactive discussion we had, the vast majority of the people who attended the session–comprised of both young professionals and seasoned executives–recognized the vast potential for social media to enhance the way people up and down the supply chain communicate and collaborate with one another; improve the way companies discover and analyze real-time information to make smarter and faster business decisions; and enable new, more efficient supply chain processes."

Because social media strategies are uniquely tied to specific companies rather than a one-size-fits-all course of action, Gonzalez concedes that it is easy to be skeptical about all the fuss and bother. The most successful social media strategies, to date, have been consumer facing. Gonzalez, however, believes that is about to change. He writes:

"Up to now, social media has been used mostly by business-to-consumer (B2C) companies to promote their brands and market their products to consumers. The early adopters have been young professionals who already use these tools in their personal lives, and the focus has been largely on enhancing external communication, mainly with consumers. Moving forward, however, more business-to-business (B2B) companies will use 'social networking' solutions (which includes not just public sites like Facebook and Twitter, but also enterprise systems like Moxie Software and Yammer) to enhance external communication and collaboration with customers, suppliers, logistics service providers and other partners, as well as improve internal communication and collaboration between co-workers and across functional groups."

In other words, Gonzalez is predicting that social media capabilities will be used to breach internal corporate silos and external supply chain opacity. He asserts that within half a decade "we won't be talking about social media in supply chain management–it will just be supply chain management." He claims that we are at a "social media inflection point." He underscored his point using the following slide.


To put it another way, social media strategies are not just about getting someone to "like you" on Facebook; or as Lora Cecere puts it, social media is "More than just a F-WORD." [Supply Chain Shaman, 13 June 2011] She fears that a social technology bubble is being created that could burst and leave disappointment in its wake if not managed correctly. She explains:

"Many of us, ... have lived through [tech bubbles] before. ... We watch them form and skeptically view the horizon as the press fills it with names and concepts that are new. There will be hype, technology pitches/marketing with over-inflated expectations, brilliant early adopters that will flash with brilliance and then fade, shortly followed by the hangover or period of disillusionment. However, ... I believe, that this bubble offers supply chain leaders great promise if we can look past the hype, side-step the early missteps, and shape the promise."

Cecere makes a distinction between "social technology" and "social media," which she believes is an end state. She believes that social technology is "more than hot air" and "is ready to take flight." She continues:

"While the press strongly touts it, I strongly believe that here is more to it than just a 'F-word'. I believe that it can be the redefinition [of] networks, a new way of defining demand processes from the outside-in, offering new possibilities to listen and have dialogue with the customer's customer, and to sense market changes with less latency. It is about a new type of technology: networks that can connect the socialgraph with personalized interests to actively communicate with micro-segments of the market. It is about dialogue."

Cecere and Gonzalez seem to be in agreement on this point: social media strategies for most companies are going to be about communication and collaboration. Cecere is concerned that some people will confuse social media strategies with eCommerce strategies; but, she insists, "the definition of the network is fundamentally different in reach than eCommerce." She explains:

"[The social technology network] provides a unique opportunity to forge relationships and influence buying behaviors based on friends of friends. Think about what is possible. … We have never had the ability to listen in near-real-time. Supply chain networks have never been based on relationships. Instead, we have depended on order to cash transactions fraught with days and weeks of latency. How could we redefine supply chains if we had technologies that could operate in a different context based on relationships with near zero latency of information. Why is this different than eCommerce? While some might argue that social is an extension of eCommerce, I disagree. The network is fundamentally different. The technology possibilities are different. ... As we look at this rising bubble, we need to ask ourselves three questions:

  1. Which are hype and which have real promise?
  2. Given the promise, how can I use these new data sources and improved latency to my advantage?
  3. Are there new ways to define technologies in networks to drive new levels of value?

Today, as I postulate the possibilities with a different set of technologies like Zyngna (gaming), Digital Portfolio (electronic list management), Groupon (social couponing), Spiceworks (sales of IT Technology through a community for the B2B audience), Bazaarvoice (content/review aggregation), ExpoTV (video reviews), I am convinced that this social bubble is growing an infrastructure that, like a bubble, takes many forms and colors before it takes flight. These disparate technologies will rise in their own separate bubbles before they coalesce."

If I correctly sense what Cecere is saying, these are the early days of social technology and so it makes sense that social media strategies are difficult to develop. It also explains why Wally's co-worker would remark that a social media strategy sounds like something that nobody wants and nobody needs. Cecere insists, however, that you should care and you do need it. She continues:

"For supply chain leaders, I believe that the social bubble has the potential to fuel more than a Facebook phenomenon. Here I share why supply chain executives should look more broadly at this technology than social media, and how to steer supply chain leadership teams through the hype cycle. ...

  • Mobile Internet is growing at 8X the rate of the web browser when Netscape launched in 1994. In 2010, there were 8.2 billion mobile applications downloaded. Kleiner Perkins forecasts that mobile traffic will grow 26X over the next five years. Mobile applications are an accelerant for social dialogue.
  • Social commerce, nascent when Altimeter launched the Rise of Social Commerce last year, is now a market. On average 65% of consumer brands have more Facebook traffic than website traffic. Buying directly from Facebook or through Twitter is an accepted practice and virtual currency and reward systems are gaining ground.
  • The use of social technologies to improve customer service is also blossoming. When it comes to defining customer service, both Facebook and Twitter have some unique advantages, and new customer service models are taking form."

Cecere points out, however, that some technology vendors are trying to jump on the social media bandwagon even though their products "have no direct connection to social commerce." Their attempts "to be cool" make no sense Cecere insists and warns, "Buyers beware." Although some "opportunities" don't make sense, she insists that many do. She explains how one can tell the difference between real and false opportunities. She writes:

"As we think about the supply chain as the flow of goods and services with minimal information latency that maximizes our cash opportunities, this wave offers new hope to redefine the supply chain to drive a step-change. However, this can only happen if we avoid the potholes:

"Social networks are not an extension of eCommerce. While many companies have entrusted their social strategies to the eCommerce team, I don't believe that social commerce is an extension of e-commerce. The fundamentals are different. Social commerce is a new channel. I believe that companies that see social technologies as an extension of e-commerce will fail to reach full potential.

"Inside-out versus Outside-in. I also don't believe that social [networks] should be owned by marketing. In fact, I think that the hype caused by social media for social's sake in marketing will give a premature death to many well-intended initiatives. Buyers just don't want to be YELLED at anymore.

"Instead, I believe that social [networking] is a way for us to truly get to know our customers, our shoppers, our buyers. You may use your favorite term–customer-centric, demand-driven, market-driven–but I believe that the real difference happens when the design of the supply chain starts from the outside in. Leaders will learn how to listen to their customers, will redesign processes to use near-real-time feedback, and the ideation cycle can be redefined to better source and use consumer insights. Instead of a blind, unintelligent, costly response called supply chain today; companies will build sensing mechanisms and learn near-real-time through test and learn systems. Seems simple enough, but while the promise is large, the answer is in the future. The concepts are vastly different than traditional supply chain management, and social technologies offer us some important technologies."

I believe that Cecere is spot on when she writes "the promise is large" but "the answer is in the future." Companies like mine are learning along with our customers how best to use data collected through social technologies as well as how to use social media opportunities to increase sales. I believe the learning curve will be steep, which is why social media commentary has been so prevalent. One of the biggest opportunities, Cecere notes, is for manufacturers to go direct to end-user customers. She writes:

"Manufacturers are trying to gain power to have more muscle with retailers and improve global presence. ... The rise of social commerce gives mid-market companies a new opportunity to build a relationship directly with the shopper and better manage the long-tail of the supply chain more easily. There is less channel friction for a manufacturer to sell directly to the customer than we saw in the evolution of eCommerce."

She does offer a word of warning, however. She states, "Social must come before Commerce." She explains:

"Social commerce – the use of social technologies to enhance and define the shopping experience – is a new channel. It is also an exciting new way to build a direct relationship with the shopper. However, it is only successful if social precedes commerce and the manufacturer builds a relationship with the shopper. It should not be seen as an extension of advertising or e-commerce. It is about building a relationship that can be enhanced by commerce. It is too important to leave in the hands of marketing."

At this point, Cecere and Gonzalez appear to diverge slightly on what the future holds. Gonzalez sees corporate collaboration and communication as the principal benefits of social technologies while Cecere sees the rise of social commerce. Both, of course, could be correct. Cecere, however, focuses on the social commerce aspect and offers a little advice. She writes:

"Be where the Action is. For a company to be successful, carefully craft your presence in four social media: Twitter (customer service and listening), Facebook (direct connection with fans), YouTube (product advocacy and usage tips) and Linked-in (for Human Resource purposes). This is important to business and defining new business processes. Forge a cross-functional group to think about how social, mobile and tags can be used to redefine supply chain, customer service, human resource processes, innovation and sourcing processes."

Although companies have good reason to be concerned about cybersecurity, Cecere believes they need to find a way for employees to employ social media at work. She writes:

"I am embarrassed when I visit promising companies and see employees interacting on social networks for business purposes off of their personal mobile devices. Supply chain is business. Social is a new way to redefine this business process. ... Train your employees on your social policy and begin the building of new supply chain processes from the outside in."

She concludes, "At the end of the day, it is about building and enhancing the relationship to improve value in the value chain. It is not about technology for technology's sake. It is not about cool toys for cool boys and girls. Likewise, don't hamstring your teams initially with Return on Investment (ROI) goals, instead invest in social technology projects when there is a promise to improve the relationship, reduce data latency and improve the context of information." There is still a feeling-out process going on when it comes to social technologies and the supply chain. Most analysts insist that there is value to be found; but, they are still not quite sure exactly where to look. Don't get discouraged. As Cecere says, the answer you are looking for may be in the future. So if you find yourself in the situation where developing a social media strategy is taking a long time, don't get stressed out -- you're not alone.

November 14, 2011

Supply Chain Complexity

The Financial Times recently asked three commentators, including good friend, Lora Cecere, to answer the question: "Do complex supply chains make you too vulnerable?" [1 November 2011] The column begins by describing some of the supply chain disruptions that have occurred over the past year as a result of earthquakes, tsunamis, floods, etc. It then asks two more questions: "Do these cases suggest that complex supply chains are the wrong strategy? Should they be unwound and simplified?"

The first respondent offering answers to those questions was Bob Lutz, former vice-chairman of General Motors and author of Car Guys vs Bean Counters. He wrote:

"Managing a supply chain is like anything else in business: a careful blend of present state, analysis and that elusive ingredient called 'gut feel', aka, the 'art' rather than the 'science'. Trying to optimise cost by buying far afield may look the best on paper (which is important to the 'bean counters'). But what happens when 'just in time' is 'just plain late'? When disruptions are caused by weather, dock strikes, natural disasters or costs swing the other way due to exchange rate changes? How about the time delay in discovering a batch of bad parts? Running your procurement purely on a short-term, point-in-time, cost-minimisation model is like shopping for rock-bottom price home insurance: it looks real smart until your house burns down!"

Can we agree that, if Lutz answered the questions posed by the newspaper, his answers were shrouded in ambiguity? Here's my best guess at what he was trying to say. Yes, complex supply chains can present challenges; however, lean, just-in-time supply chains can be brittle. A case in point about lean supply chains was published in the paper the same day as Lutz' answer. The headline read: "Thai floods force Honda to cut US production." [John Reed, Financial Times, 1 November 2011] Since we receive no definitive answer from Lutz beyond going with our gut, we look to the next respondent for answers. The next commentator, Bob Fischer, comes from academia. He is a professor of technology management at IMD. He wrote:

"Key strategic choices are all about execution and this typically means supply chain competitiveness. Think Benetton, Zara, Dell, Frito-Lay, Li & Fung. Nokia's amazing run over 20-odd years was partly attributable to supply chain smarts, and Nespresso's current success certainly is. Being able to quickly implement contingency plans through knowledge, trust and agility along a value chain is much more important than building-in 'what if' compromises to anticipate disruptions. Great supply chain performers such as Samsung, Hyundai and Rolex do this by supporting their value-chain partners rather than squeezing them."

Apparently we are not going to get any straight answers to the questions regarding supply chain complexity. I'm a bit set back by the professor's dismissal of "what if" planning. You can't really make good contingency plans without some "what if" planning. That is how you gain the "knowledge, trust, and agility" that he thinks is so important. Although Fischer didn't answer the questions about supply chain complexity, he did reiterate the importance of supply chain collaboration. Collaboration involves sharing essential information that makes supply chains more transparent. Visibility goes a long way towards making complex supply chains easier to unravel and manage. Lora Cecere, a partner at the Altimeter Group, was the final respondent. She wrote:

"Even when events such as the Japanese earthquake, floods in Thailand, and political unrest make headline news, the great supply chains shift and carry on. However, many others cannot because their tightly integrated systems do not allow supply chain managers to sense and drive an adaptive response. While many will cry that cataclysmic events and subsequent shortages are reasons to 'near-source' by shortening the chain, it is important to note that 'shift happens' in all parts of the world. The answer lies in better supply chain design and 'what-if' planning and suppliers who can sense and adapt to change. Resilience must also be part of the design."

Finally a more direct response to the questions. You don't have to read too closely between the lines of Lora's short write-up to understand her answers. Do complex supply chains make you too vulnerable? Yes, but any supply chain is vulnerable to disruption. Do these cases suggest that complex supply chains are the wrong strategy? No, they suggest that supply chains need to be transparent and agile. Should they be unwound and simplified? Probably. I know that Lora believes that because she wrote a post entitled ["Untangling the Chains," Supply Chain Shaman, 8 August 2011] In a post entitled Reducing Supply Chain Complexity, I discuss Lora's thoughts as well as those of other supply chain analysts.

I found it interesting that folks at the Financial Times described complex supply chains as a strategy (i.e., "Do these cases suggest that complex supply chains are the wrong strategy?"). I can't imagine a group of supply chain professionals sitting around a conference table insisting that they need to make their supply chains more complex as a matter of strategy. A corporate strategy may be to obtain parts from numerous global sources to make the finished product more acceptable in countries from which parts are drawn; but, in such a case, a marketing, rather than a supply chain, strategy is the driver. Complexity is the consequence of other decisions rather than being a deliberate strategy on its own. A quarter of a century ago, D.J. Bowersox and P.J. Daugherty identified three basic supply chain strategies. ["Emerging Patterns of Logistical Organization Journal of Business Logistics, 8 (1), 1987, 46-60] Daniel Dumke, writing about their study, states:

"Do supply chain strategies evolve over time? Are there the same strategic options nowadays compared to 20 years ago? Since at least the meaning of the term logistics has evolved during the last 20 years, especially due to the emergence of supply chain management, logistics and supply chain management are used interchangeable in this article. In 1987 Bowersox and Daugherty created a logistics strategy framework, concluding that there are basically three SC strategies:

  • Process Strategy -- management of the traditional logistics activities with a primary goal of controlling costs.
  • Market Strategy -- management of selected traditional logistics activities across business units with the goal of reducing complexity faced by customers.
  • Information Strategy -- management as a system, with the goal of achieving inter-organizational coordination and collaboration through the channel.

["Analysis of Logistics Strategies from 1990 to 2008," Supply Chain Risk Management, 21 March 2011]

I found it very interesting that analysts were talking about information strategies and collaboration at the dawn of the PC era. The reason they were, of course, is that the cost of computing was starting to plummet. That same year that Bowersox and Daugherty published their study (1987) Al Fasoldt wrote:

"In less than 10 years, the retail price of a 64-kilobyte Atari 8-bit computer and its peripherals has fallen from $4,000 to $250. Computers that are no longer being made offer even more dramatic comparisons; some that cost many thousands of dollars a few years ago are now being sold for a few hundred dollars." ["Flashback: Computer pricing, 1987," Technofile]

At the time, Fasoldt mused that a decade later (i.e., in 1997) a computer would cost around $25. He would probably have been correct had people been making 64-kilobyte 8-bit computers. The point is, supply chain collaboration and visibility were perceived as a good thing to achieve even 25 years ago. Why? The answer is: Because supply chain professionals understood that supply chains were going to become increasingly complex and they knew they would need help dealing with that complexity. I don't think many (if any) companies use one of Bowersox's and Daugherty's strategies exclusively. Every company I know uses a combination of those strategies. That is where the "art" comes in that Lutz wrote about. Dumke continues:

"Building on this framework [M.A.] McGinnis, [J.W.] Kohn, and [J.E.] Spillan executed and analyzed four surveys from the years 1990, 1994, 1999, 2008 with the above mentioned research questions in mind. ["A Longitudinal Study of Logistics Strategy: 1990-2008 Journal of Business Logistics, 31 (1), 2010, 217-235] The following hypothesis were designed:

  • Importance of Bowersox framework remained constant
  • Dependent variables (statistical data on the survey participants like: logistics coordination effectiveness, customer service commitment and competitiveness) remained constant
  • Within a logistics strategy, process strategy, market strategy, and information strategy will be of equal importance.

"First, the results show, that the dependent variables and the perception of the strategies did not change too much to make a comparison between the studies impossible. To analyze the results further the authors clustered the respondents into three strategy clusters (intense, intermediate and passive cluster), depending on their propensity for the mentioned strategies. Here is what they found:

  • Intense Logistics Strategy increased -- That means that either the importance of logistics strategy in U.S. manufacturing firms increased in importance or the firms were more intensely managed overall, including logistics.
  • Relative Importance -- Process strategy (cost control) is generally more important than market strategy (reducing complexity faced by customers), and that both are more important than information strategy (inter-organizational cooperation and collaboration).

Frankly, I found those results a bit surprising. Based on comments from analysts like Bob Ferrari, perhaps I shouldn't be surprised. In a number of posts, Ferrari has decried the fact that executives look at the supply chain as the best place to cut costs. Those efforts, he insists, have left supply chains more brittle than they should be. The fact that the information strategy was the bottom of the heap explains why so many companies still don't have very good supply chain transparency. As I concluded in my post mentioned above, "The bottom line is while are some things that can be done to reduce supply chain complexity, like shortening supply lines and segmenting supply chains; however, the biggest gains are going to be made from increasing supply chain understanding rather than reducing supply chain complexity. Good decision tools can make decision choices easier to understand in a complex world by helping make sense of the complexity itself."

November 11, 2011

To Innovate the U.S. Must Manufacture

The twentieth century was almost universally recognized as the American century. There were numerous reasons for that; but, high among them was the fact that America was known as a country of innovators. Louis Uchitelle argues that the American century started to ebb when its factories started to close. Although Uchitelle begins by making an economic argument, another point he eventually makes is that a lot of innovation disappeared when the factories went away. ["When Factories Vanish, So Can Innovators," New York Times, 12 February 2011] He writes:

"Losing an industry or ceasing to manufacture a particular product ... has indeed become a fairly frequent event. Just in the last few years, the last sardine cannery, in Maine, closed its doors. Stainless steel rebars, the sturdy rods that reinforce concrete in all kinds of construction, are now no longer made in America. Neither are vending machines or incandescent light bulbs or cellphones or laptop computers. Less noticeably, American manufacturers are importing more of the components that go into their products. The imported portion has risen to more than 25 percent from 17 percent in 1997, according to Susan Houseman, a senior economist at the W.E. Upjohn Institute in Kalamazoo, Mich."

Uchitelle, for example, singles out the Boeing Company. "Boeing ... once bought all of its components from American suppliers or made them in its factories here," he writes. "Now the wings of several of its airliners are manufactured by Japanese subcontractors and shipped across the Pacific in giant cargo planes." There are reasons that parts are being imported beyond the search for lower cost manufacturing. No one can claim that Japan, for example, is a low-cost country. The reason that Boeing uses so many foreign parts is because it wants to sell its aircraft all over the globe. That is a much easier task when it can show that buying a Boeing product creates jobs in the target country. Nevertheless, Uchitelle's argument, that foreign components are used more widely in U.S. products today than in the past, remains true. The reason this concerns him is because he believes it skews GDP figures. He explains:

"An accurate count would reduce manufacturing's share of the gross domestic product, or total national output, to less than the 11.2 percent that the Bureau of Economic Analysis has reported through 2009, the latest figure available. That 11.2 percent would be closer to 10.5 percent, if all of the imported components were counted as imported instead of domestically made. Even the 11.2 percent figure is down sharply from the 14.2 percent share of just a decade earlier, and the nearly 30 percent of the heyday 1950s, when almost every product bought by Americans was also made here. Concern is increasing that this decline has gone too far. 'I think there is a growing recognition that a diminished manufacturing sector will undermine our economy,' says Mark Zandi, chief economist for Moody's Analytics."

Uchitelle explains that American companies gambled that profits would increase ("without any sacrifice in product quality") by shifting manufacturing jobs from the U.S. to low-wage workers abroad. By doing so, they also gambled that "American manufacturers ... would be the world’s best innovators, developing sophisticated new products here at home and producing them, at least initially, in their domestic factories." So how did the gamble pay off? Uchitelle provides his perception:

"The first part of the arrangement worked very well. Consumer prices did fall as imports flooded in — from foreign manufacturers, of course, but also from factories newly opened abroad by American multinationals. The flood was so great that President Ronald Reagan in the 1980s placed temporary quotas on Japanese autos and motorcycles, and tariffs on selected electronic devices. The second part of the arrangement, however, has been more problematic. As it turns out, the United States is not the only path-breaker. The Toyota Prius, the first hybrid, shines as an example of Japanese ingenuity, and more than a decade after that car was developed it is still being exported from Japanese factories, marrying innovation to production and jobs. The iPad and the iPhone, developed by Apple in the United States, are spectacular technologies. But the devices themselves are made in Asia, not America. And as time passes, the people who make the iPad and the iPhone day after day — the engineers and factory workers in Asia — may produce the next innovations. Or so many experts are coming to believe, including Ms. Houseman."

That is the crux of Uchitelle's argument. We are helping create innovators, but those innovators now live overseas. Houseman told him, "The big debate today is whether we can continue to be competitive in R&D when we are not making the stuff that we innovate. I think not; the two can't be separated." If Houseman is correct, and she may be, then a lot of business leaders and policymakers need to reconsider the path U.S. manufacturing takes in the future. The thrust of Houseman's argument is that lost jobs represent more than just lost wages and lost taxes. They represent lost knowledge and lost opportunity. Uchitelle concludes:

"While consumers have benefited from lower prices, made possible by unrestricted imports, on the other side of the ledger are tens of billion of dollars in lost manufacturing wages. Something else is gone, too. 'We had a storehouse of knowledge and skill built up in these workers and we can't use it now,' says James Jordan, president of the Interstate Maglev Project, promoting a high-speed rail technology that uses special magnets to levitate and propel trains. Maglev was invented in the United States, but equipment based on that technology is manufactured and used today in Japan. Mr. Jordan argues that as manufacturing's presence — and status — shrinks in America, the odds of a Henry Ford or a Thomas Edison or a Steve Jobs appearing in the next generation are reduced. Certainly people like Mark Zuckerberg of Facebook are inventors, though not of physical products. 'Young people stop thinking about making things,' Mr. Jordan says. 'It is no longer in their heads. They have a different mental orientation.'"

It seems to me there are two different arguments here. The first argument is that lost manufacturing jobs represent the loss of knowledge and skills embodied in workforce. Frankly, this is not as strong an argument as it once was. Many of the manufacturing jobs that were lost were manpower intensive jobs that required some skill, but little knowledge. Other jobs were given to robots rather than other human beings. The manufacturing jobs that are returning to the U.S. don't demand the same skills as the jobs that were lost. Perry Sainati, founder and president, Belden Inc., writes, "I take a backseat to no one when it comes to appreciating the role that manufacturing plays in this country's economy. But then again, anyone who believes that a pronounced uptick in this country's manufacturing output will immediately translate into a full-scale spike in job growth just doesn't understand the fundamentals of manufacturing." ["Your Grandfather's Manufacturing Jobs 'Ain't Comin' Back'," Industry Week, 7 July 2011] Concerning the manufacturing jobs that will return, he writes:

"[The types of manufacturing jobs that once defined the American workforce] are gone. What's more, as Bruce Springsteen once sang, 'they ain't comin' back.' That's not to say, of course, that manufacturing growth will not continue to translate into meaningful job growth -- and meaningful careers -- in this country. Because it will. It's just that it won't translate into the massive quantities of jobs people still want to believe are possible. Nor will it translate into the kind of low-skilled jobs that once defined the assembly line dynamic. In this day and age, companies like mine simply cannot afford to pay top dollar for workers whose skill sets do not extend beyond the ability to spot weld a piece of metal or maybe torque down a bolt or two."

The second argument is much more compelling; namely, young people are no longer thinking about making things. That has to change. On that point, I'm in full agreement with Uchitelle, Houseman, and Jordan. On the other hand, I'm not altogether despairing either. In several past posts, I discussed how some of the nation's best schools, like the Massachusetts Institute of Technology, have very popular courses in which some of the world's best teachers (from different disciplines) and some of the brightest students (from different majors) engage to make things that help solve some of the world's most difficult challenges -- like clean water, green energy, etc. For example, several years ago I discussed an MIT program that was seeking solutions to challenges facing the world's poor. ["Low Technologies, High Aims," by Andrew C. Revkin New York Times, 11 September 2007]

"Beneath the bustling 'infinite corridor' linking buildings at the Massachusetts Institute of Technology, just past a boiler room, an assemblage of tinkerers from 16 countries welded, stitched and hammered, working on rough-hewn inventions aimed at saving the world, one village at a time. M.I.T. has nurtured dozens of Nobel Prize winners in cerebral realms like astrophysics, economics and genetics. But lately, the institute has turned its attention toward concrete thinking to improve the lives of the world's bottom billion, those who live on a dollar a day or less and who often die young."

The behind-the-boiler workshop was part of "a four-week International Development Design Summit to identify problems, cobble together prototype solutions and refine the results to see which might work in the real world." There are simply not enough of these cross-discipline kinds of courses and they need to be conducted for U.S. students, not just international students. Once a student feels the satisfaction of inventing and building something for himself, the bug seldom leaves them. Another effort with that aim that deserves more attention is a program called FIRST (For Inspiration and Recognition of Science and Technology). The organization was founded in 1989 by inventor Dean Kamen to inspire students in engineering and technology fields. The students get to build things. We need more programs like FIRST.

Alan Murray, deputy managing editor of The Wall Street Journal, wrote a review about a book entitled The Comeback by Gary Shapiro. He writes:

"Mr. Shapiro focuses on innovation, which he argues is the nation's great competitive advantage, the source of American exceptionalism. It is easy to think of innovation as something that just happens, but it is in fact embedded in a social and political matrix. Innovation, Mr. Shapiro writes, 'is the fortunate result of our nation's rich and unique stew of individual liberty, constitutional democracy, limited government, free enterprise, social mobility, ethnic diversity, immigrant assimilation, intellectual freedom, property rights and the rule of law. I can't deconstruct how each factor makes its individual contribution, but I believe each is vitally important.' But policies need to make the most of such exceptional assets, Mr. Shapiro observes, and too often they don't. In 'The Comeback' he details the policies that, he believes, will allow innovation to flourish. His recipe is a familiar one but not yet familiar enough to engage the preoccupied minds of warring political parties in Washington."

One thing Shapiro doesn't mention is manufacturing -- probably a mistake. He does, however, vent about education. Murray continues:

"Mr. Shapiro ... thinks that it's an outrage that the U.S. ranks near the bottom among developed nations in math and science education. He doesn't say quite what we are supposed to do about such a failure."

James Jordan might argue that we need to teach students how to make things. In other posts, I have argued that we need to teach students how to solve problems (see Teaching Problem Solving Skills in Math and Science, Part 1 and Part 2). Apparently Shapiro advocates "teaching more 'business and entrepreneurialism,'" beginning in high school. I'm inclined towards notion that we need to reinvigorate the spirit of manufacturing among our young people. That probably begins by helping them learn the joys of invention, which leads to innovation and manufacturing. Jennifer M. Granholm, a former governor of Michigan, asked, "Do we want in this nation to lose the backbone of manufacturing in this country? Do we want to be a nation that doesn't want to manufacture anything?" Hopefully, the answer to that question is a resounding "no." One thing we do know is that we are not inspiring our youth to go into engineering, math, or sciences. Recent articles report that students still favor liberal arts majors even though they lead to poorer paying jobs. ["Generation Jobless: Students Pick Easier Majors Despite Less Pay," by Joe Light and Rachel Emma Silverman, Wall Street Journal, 9 November 2011] We need to turn that around if America is going to remain the world's leading country for innovation.

November 10, 2011

Business Heads for the Clouds

Rolfe Winkler writes, "After burying its head in the sand, Oracle is finally looking skyward. Better late than never for shareholders." ["Oracle Embraces Cloudy Future," Wall Street Journal, 25 October 2011] Winkler was responding to Oracle's "$1.5 billion acquisition of RightNow, a cloud provider of customer-service software." Winkler notes that it is not surprising that Oracle is coming late to the cloud-computing game. After all, he writes, "Chief Executive Larry Ellison famously pooh-poohed cloud computing, calling it 'complete gibberish' in 2008." To be fair to Ellison, I suspect he was referring more to the "cloud" illusion than to the concept behind on-line services. His actual quote was:

"The interesting thing about cloud computing is that we've redefined cloud computing to include everything that we already do. I can't think of anything that isn't cloud computing with all of these announcements. The computer industry is the only industry that is more fashion-driven than women's fashion. Maybe I'm an idiot, but I have no idea what anyone is talking about. What is it? It's complete gibberish. It's insane. When is this idiocy going to stop?"

Much to Ellison's chagrin the term "cloud computing" has stuck and it is unlikely to fade away any time soon -- nor, unfortunately, are his comments about it. Winkler notes that one reason Ellison might have wanted to downplay cloud computing is because Oracle has a significant portion of its business dedicated to non-cloud applications -- and those applications are vulnerable. He continues:

"Not all of Oracle's software business is threatened by cloud computing, but it still makes sense to adapt. Even if Oracle sells software cheaper in some vulnerable areas, it is better to embrace the new business model than allow parts of its business to dwindle."

Oracle will undoubtedly end up embracing cloud-computing. Earlier this year, an IBM study that involved "more than 3,000 global CIOs" reported "that 60 percent of organizations are ready to embrace cloud computing over the next five years as a means of growing their businesses and achieving competitive advantage." ["New Global IBM Study Confirms Cloud Computing Poised to Take Off at Companies," Small Business Trends, 21 May 2011] That is a money-flow into which Oracle, and most other service providers, want to jump. The IBM press release continues:

"As demand for ever-growing amounts of information continues to increase, companies are seeking simple and direct access to data and applications that cloud computing delivers in a cost-efficient, always-available manner. The use of cloud, which began in supporting deployments mainly inside companies, has now also grown common between organizations and their partners and customers."

Of course, it's not just access to information, or the sharing of it that is important, it's deriving actionable intelligence from it. It is no surprise, therefore, that "the IBM study also found that more than four out of five CIOs (83 percent) see business intelligence and analytics as top priorities for their businesses as they seek ways to act upon the growing amounts of data that are now at their disposal."

Another corporate giant, Microsoft, also sees its future in the clouds. The company "is pivoting to cloud computing from traditional computing [as] part of a sweeping revision of the software giant's business model." ["Ballmer Is 'Re-Imagining' Microsoft Around New Forms of Computing," by Steven D. Jones, Wall Street Journal, 14 September 2011] Jones writes:

"Chief Executive Steve Ballmer said ... that Microsoft is 're-imagining' every part of its software empire to run on and through the cloud. ... [He said] that Microsoft's core computer operating system was being recast as a 'powerful cloud' operating system capable of delivering a rich inventory of Microsoft software in forms and sizes any device from a desktop computer to a phone can handle."

Jones points out that one reason that Microsoft is transitioning to the cloud is because it is scrambling "to create software for a booming mobile device market. Sales of smartphones and tablets are starting to affect those of conventional computers, most of which run Microsoft's operating system." Jones continues:

"Cloud computing moves software and data storage onto remote servers operating behind corporate firewalls or on public networks owned by companies such as Microsoft, Google Inc. and Inc. Google and Amazon also are expanding into Microsoft's turf by offering services such as document sharing and email. Delivering services through a cloud reduces reliance on a computer operating system such as Windows, which is Microsoft's core business. Committing to the cloud also creates another way for Microsoft to fight back against competitors who say we are entering a post-PC world."

Because corporate giants like IBM, Oracle, Google, and Amazon are garnering the lion's share of attention when it comes to cloud-based service providers, business owners could easily conclude that only large businesses are able to benefit from those services. Carol Kline and Tina Valdez report, however, that large businesses are not the only companies that benefit from cloud-based services. ["SMBs and the Cloud: Size Does Not Matter," CRM Buyer, 17 October 2011] Kline and Valdez claim, "As customers become more digital, social and mobile, small and mid-sized businesses have significant opportunity to improve customer satisfaction and loyalty through a differentiated customer experience, just like their enterprise competitors. However, those who are unwilling to invest in solutions that embrace the needs of today's marketplace will most certainly be left behind." No business likes to believe that it is the tail being wagged by technology's head, but Kline and Valdez ask business leaders, especially slow adopters, to "consider these facts":

  • More than 2 billion consumers are online, spending more time online than watching television, and only 28 percent of consumers prefer to resolve service issues on the phone.
  • 96 percent of Gen Y has joined at least one social network, and, in 2010, they outnumbered the Baby Boomer generation.
  • By 2015, mobile Internet will surpass fixed Internet, and 40 percent of 18-34 year olds use their mobile devices to make purchases today.

Kline and Valdez call these facts the "new realities" that need to "shape customer management strategies." They are also facts that have "many small and medium businesses ... scrambling to find solutions that meet customer needs without onerous investment and infrastructure requirements." Kline and Valdez report that some small- and medium-sized business owners perceive cloud-computing as a money pit rather than a foundation upon which to grow their business. This perception, they write, is "based on the assumption that integrating a full-service cloud solution requires complex relationships with multiple service providers." They continue:

"Thankfully, that's just not the case. ... Until the application of hosted -- or cloud -- technology, many advanced customer relationship management solutions were out of reach for small and mid-size operations. But done right, cloud technology and a smart cloud channel strategy stand to be huge enablers of competitive advantage through a differentiated customer experience. More businesses are recognizing this opportunity and taking advantage of the benefits of cloud-based contact center solutions, improving customer satisfaction and return on investment by as much as 27 percent in the process."

That double-digit figure ought to get a few business owners to pay attention. That figure also begs the question, "How can the cloud help small and medium businesses compete and better identify, attract and serve customers?" Kline and Valdez not only ask that question they offer "six benefits you can't afford to ignore":

"1. Reduced fixed and technology support costs, all with access to new technologies at lower risk. In large organizations, acquiring and maintaining traditional physical infrastructure -- including data centers, as well as separate contact center technology at each service delivery center -- requires significant capital expenditures. Organizations are then often committed to a system for the depreciable life of the assets, limiting the ability to try new solutions or make significant changes. Cloud solutions allow companies to pilot, implement, and globally scale without incurring unacceptable levels of risk."

In other words, cloud-computing can help you reduce sunk costs in what will surely become legacy systems. The second benefit relates to customer service.

"2. Improved customer satisfaction and revenue by delivering a consistently great experience and the right service at the right time via the right channel. A key driver in customer satisfaction is the ability to recognize and accommodate customers from one channel to the next. This nimble and proactive approach requires a partner that can deliver a centralized and virtualized infrastructure that allows for one view of the customer across all channels, including mobile and social channels."

Not only can you get great solutions, those solutions are created by subject matter experts who most small- and medium-sized could never afford to hire. Getting back to money savings (which increases ROI), Kline and Valdez note another benefit is reduced onboarding costs.

"3. Reduced onboarding costs, higher retention and better associate performance. A virtual, global system broadens the talent pools exponentially, and allows companies to select the most qualified associates. Once these associates are in place, they are armed with the best possible training and knowledge. This occurs via a crowdsourcing approach to learning and customer intelligence, along with the cross-channel visibility mentioned above, making for a powerful customer experience."

Benefit four is also staff-related:

"4. Reduced cost-to-serve via improved staff utilization, effective multichannel strategies, and access to new tools that improve operational efficiency. While a non-technical telephone contact can run as high as US$12, self service can be as little as $0.10 per contact, with click to chat, email and virtual agents costing anywhere from $1 to $5 per contact. Cloud solutions make it possible to balance these options and deliver sales and service via the right mix of channels to various customer profiles. As a result, average cost per contact can be reduced by 44 to 88 percent. Only cloud-based contact center solutions give non-enterprise organizations the chance to try multichannel solutions without the risk and investment. But when doing so, companies will be best served by selecting a provider that has the experience running the technology themselves, so they can serve as a professional advisor rather than merely the company that delivers the technology."

My only caveat here is that companies need to make sure that technology improves customer service rather decreases it. Many customers view technology-based customer services as dehumanizing and infuriating. Kline and Valdez next discuss one of the most important benefits of cloud-based services -- scalability.

"5. Improved responsiveness and scalability, across channels, and around the globe. In the highly seasonal retail industry, for example, premises-based systems and traditional workforce management mean idle human resource and technology costs during non-peak times. Meanwhile, unanticipated or particularly high demand can result in missed opportunities and a poor customer experience. Cloud architecture enables ready and flexible access to the right associate talent pool."

Their final benefit is closely related to reduced onboarding costs:

"6. Reduced implementation timeline with fast time-to-market and time-to-benefit. Cloud-based solutions allow companies of all sizes to respond to dynamic market changes in real time. This allows companies to more easily make decisions based on market opportunities or competitive threats, ultimately delivering a more timely, and higher quality experience to customers."

In conclusion, Kline and Valdez write, "Companies large and small stand to benefit from the flexibility, scalability and efficiency that cloud contact center solutions deliver. By leveraging the cloud to create a superior customer relationship management strategy, companies can drive down costs and improve revenue, loyalty and retention through a differentiated customer experience." With all sizes of companies heading for the clouds, Gartner analysts Drue Reeves and Daryl Plummer ask several important questions: Is Cloud Computing too big to fail? [Financial Times, 17 October 2011] They write:

"Liability – it's a word you don't hear in most cloud discussions, but you might want to start introducing the topic. In the cloud world, questions of who's liable for business failures and how much compensation can be expected are often overlooked. So, how do you know if you're covered or not? The issue is concentration risk and stacked liability. What if one cloud provider got so many big companies (or companies in an industry) and then failed? Could this affect us all? Could it affect the economy? Could a cloud provider become 'too big to fail?'"

I think those are tantalizing questions on which to end. We'll take up the topic in a future post.

November 09, 2011

The Growing Importance of Supply Chain Analytics

Dawn Mathew Varghese, a Senior Consultant at Infosys, writes, "Supply Chain Analytics is a very hot topic today and has gained considerable mindshare among our customers too." ["Supply Chain Analytics Fact, Fiction or Fantasy," Supply Chain Management, 14 June 2011] Varghese goes on to assert that the term "supply chain analytics" means different things to different people. She compares the current situation to the old Indian fable of the blind men who were asked to describe an elephant. She continues:

"Too many areas/subareas have been attributed to analytics and [have] claimed to be a part of analytics. Broadly what analytics leads to is superior business performance through data driven intelligence. In order to achieve the different levels of intelligence (simple to advanced predictive analytics), it requires an organizational dimension based on inputs in terms of Processes, Policies, Procedures and Practices. ... Also it requires a computational dimension fired by data. Both of these dimensions form the basis of the analytical intelligence an organization can leverage on. It is this intelligence which leads to insights for a supply chain planner or a warehouse manager for him/her to act upon in such a way that it leads to superior performance."

Varghese touches on several important points. First, analytics is not about computational power (although that matters) it's about turning data into knowledge. Data cannot be obtained only from structured sources, but it must also be drawn from her 4Ps (i.e., processes, policies, procedures, and practices). Some (or most) of that data is unstructured, which makes it much more difficult to include in the supply analytics process. Excluding unstructured data, however, provides an incomplete picture and could lead to erroneous results. It certainly doesn't lead to better knowledge. Second, Varghese is right that the best analytics have an organizational dimension. I would go further and state that all business intelligence (BI) needs to be drawn from the same pool of data, whether it be used for supply chain purposes or any other business activity. As supply chain analyst Lora Cecere has commented, data should collected once and read many times. You will never achieve corporate alignment if everyone is using different data sets. Finally, good analytics requires good data. From the beginning of the computer age, people have understood the adage "garbage in, garbage out." Varghese continues:

"Organizations worldwide are keen to capitalize [on] this new way of doing business. Organizations that started with merely reporting ... are today looking at exploiting analytical prowess to have end to end visibility into the extended supply chain [in order to] enable management by exception."

She points out that a good automated system will allow decision makers not only to track shipments but determine if they are going to be late and why. Such a system will also be able to provide insights into future consequences of disruptive events, like earthquakes or hurricanes. She continues:

"Today's Supply Chain innovators are trying to be pro-active and are clearly heading towards a notch higher than management by exception. Classical management by exception is the fundamental premise for all Supply Chain Visibility programs. This is enabled by defining events based on the business process, understanding and establishing norms which fit into the definition of an exception and generating action points (based on breaching/meeting of norms) for supply chain managers. This framework [is] encapsulated in most IT enabled supply chain solutions today [and it] is helping organizations to drive an end to end visibility of their supply chain. The information derived out of historical data can further be organized, sliced, diced and served on a dashboard for insights into key performance indicators."

The importance of business intelligence visualization should not be underestimated. With mountains of data being generated and analyzed, analytical insights are only useful if they get into the right hands in the right format at the right time. Visualization expert Stephen Few writes, "Big, old, traditional BI companies are good at producing technologies that enhance the infrastructure of business intelligence—more and faster—but not the actual use of data in ways that lead to greater intelligence." ["Old BI and the Challenge of Analytics," Visual Business Intelligence, 7 March 2011] He says that to be useful, BI systems must "support decision making: data exploration, sensemaking, and communication." In order to achieve this objective, systems must focus as much on "the humans who use it" as on the technology that drives it. Varghese claims, "Few Supply Chain and collaboration heavy businesses, like 3PL companies, are exploiting visibility and analytics as a strategic weapon by conceptualizing a control room/tower (akin to an air traffic control room or a turbine control room of a nuclear station) which will give them round the clock visibility to the extended supply chain, help monitoring supply chain events and KPIs and help control and mitigate risks them to a large extent." To learn more about the concept of "control towers," read my post entitled Have You Heard about Supply Chain Control Towers?

The editorial staff at Supply Chain Digest believes that analytics can help manage inventory in a more sensible and cost effective way; but, even with good analytics, managing inventory is daunting challenge. ["Can Smarter Analytics and Optimization Finally Reduce the Out-of-Stock Challenge in the Consumer Goods to Retail Supply Chain?" 25 May 2011]. The authors write:

"For at least two decades, consumer goods manufacturers and retailers alike have been focused on reducing inventories and out-of-stocks on store shelves through such initiatives as Efficient Consumer Response (ECR), Collaborative Planning, Forecasting & Replenishment (CPFR), RFID and other programs - with somewhat mixed results. While each of the programs delivered some of the expected results, that was usually accompanied by the sense that some of the potential benefits from these initiatives were left on the table. In fact, inventory levels in consumer goods manufacturers stayed flat throughout most of the 2000s, and out-of-stock levels at the shelf have also been resistant to improvement."

Through interviews I've had with corporate executives, I can attest to the fact that these challenges remain. Reducing inventories and out-of-stocks on store shelves are areas with which executives have asked my company to help. The SCD article continues:

"A well-publicized 2007 study by Dr. Thomas Gruen of the University of Colorado and Dr. Daniel Corsten of the IE Business School Madrid, based on funding from Procter & Gamble, estimated that manufacturers lose something close to $100 billion in sales annually due to out-of-stocks at the shelf. Solving the out-of-stock challenge can therefore pay big financial dividends - especially for the companies that can reach new levels of in-stock performance first, before competitors do."

A hundred billion dollars in lost annual sales due to out-of-stock situations is an amazingly large number. Neither manufacturers nor retailers are happy losing that kind of business. The SCD staff notes that this doesn't have to be the case. It reports that "one beverage company IBM recently worked with was able to increase its sales by 12.3 million cases by significantly reducing its out of stocks, in this case throughout its distribution network that served local stores." It was able to accomplish this through better analytics -- specifically using inventory optimization software. The article continues:

"What is inventory optimization software? In short, it is a tool that looks at how inventory should best be positioned at different nodes and levels of the supply chain holistically, rather than just optimizing each node/level individually, as is the case in most traditional supply chain planning environments. The result can be significant reductions in inventory with constant or even improved customer service levels."

In other words, inventory optimization software helps determine where the inventory is and where it should be. By getting the analytics correct, inventory velocity can be increased and out-of-stock situations can be reduced -- a win-win-win for suppliers, retailers, and customers. The article continues:

"One place to start with inventory optimization is an analysis that shows not only what SKUs have too much inventory ... versus demand, but also what SKUs have too little. ... [Better inventory management] is accomplished by changing inventory policies and safety stock rules for these SKUs at different levels of the supply chain. [IBM' Dr. Michael] Watson ... noted that the SKUs that have too little inventory usually result in costly mitigation strategies, such as last minute production schedule changes or expedited transportation. Of course, no company plans to have too much inventory of some SKUs and too little for others. Then why is it so hard to get network inventory levels right?"

The simple answer to that question is: because too many supply chains don't have enough visibility. The article goes on to discuss a "number of variables that must be considered," including:

• Forecast error and demand variability
• Lead time and lead time variability
• Order and production cycles
• Committed times from manufacturing or vendors
• Transit times and transit variability
• Order minimums and increments

The article notes that this is not a simple matter because "those factors must further be considered across increasingly complex supply chains that have multiple levels or 'echelons' and often involve multiple production steps (e.g., intermediate good production, then co-packing operations)." It continues:

"It is this total complexity that almost requires strong technology support to manage, as optimizing across all these variables for hundreds or thousands of SKUs is beyond what humans and spreadsheets can accomplish."

I'm surprised the SCD staff wrote that this complexity "almost" requires strong technology support. It definitely requires strong technology support. Numerous supply chain analysts are pushing the notion that supply chain complexity must be decreased. In many cases, believing that can be done is irrational. However, the proper use of supply chain analytics can provide the perception that the complexity has been reduced because the technology deals with the complexity and displays only pertinent knowledge.

Dr. Watson told the SCD staff something that I have been stating for some time, "Lean manufacturing strategies can also sometimes conflict with overall inventory optimization." When a system becomes too lean it becomes brittle. This is not a good trait when most supply chain analysts believe that the best supply chains need to be agile and flexible. The article provides an interesting example of how a lean practice can actually cost money. The article concludes:

"Efforts to decrease raw material levels at the plant along Lean concepts can actually result in more finished goods inventory in the network, which is more costly than raw materials or WIP inventories further back up stream. Inventory optimization will help identify that optimal balance and where inventory buffers are most effectively maintained. Watson also noted that the right approach to inventory optimization means companies will check plans and inventory policies at different 'cadences' throughout the year. For example, more strategic looks at the role of inventory in a business unit might be performed annually, while more parameter 'tuning' activities might be performed quarterly, monthly or even weekly depending on the type of task."

A good BI system can help determine what cadences are required as well as help with inventory allocation itself. The bottom line is that big data is becoming more available and, when used correctly, this data can help companies more effectively manage their inventories to save money and increase sales.

November 08, 2011

Artificial Intelligence and the Era of Big Data

Despite initial reports that Apple had disappointed everyone by introducing the iPhone 4S instead of the much-rumored iPhone 5, the iPhone 4S has achieved excellent sales. One of the reasons is the new feature included with the phone called Siri a "smart voice recognition software, capable of intuitively answering a wide array of questions from iPhone users." ["Apple's Siri and the Future of Artificial Intelligence," by E.D. Kain, Forbes, 15 October 2011] Alexis Madrigal, a senior editor at The Atlantic, reports that Siri is "a voice-driven artificial intelligence system created with DARPA funds and, ... if the hype holds up, the software will be the biggest deployment of human-like AI the world has seen." ["Siri: The Perfect Robot for Our Time," 12 October 2011] Before continuing with a discussion of Madrigal's thoughts, I offer a quick primer on artificial intelligence. According to an Oracle site, "Artificial Intelligence (AI) is the area of computer science focusing on creating machines that can engage on behaviors that humans consider intelligent." Such a definition begs the question, "What is intelligence?" Professor John McCarthy from Stanford University writes this about intelligence:

"Intelligence is the computational part of the ability to achieve goals in the world. Varying kinds and degrees of intelligence occur in people, many animals and some machines. ... Intelligence involves mechanisms, and AI research has discovered how to make computers carry out some of them and not others. If doing a task requires only mechanisms that are well understood today, computer programs can give very impressive performances on these tasks. Such programs should be considered 'somewhat intelligent'." ["What is Artificial Intelligence?" 12 November 2007]

Armed with that brief explanation, let's continue with Madrigal's thoughts about Siri. He writes:

"The difference between Siri and what came before is massive amounts of data. Data allowed the construction of algorithms that decipher voice. Data on the Internet allows Siri to have a lot more situational awareness than it would have had in the past. Data about your location massively increases the usefulness of anything an assistant could offer."

In other words, Siri is another indication that we are indeed entering the Era of Big Data. For more discussion on the Era of Big Data, read my post entitled, The "Big Data" Dialogues, Part 6. Concluding his article on Siri, Madrigal writes:

"The genius of Siri is to combine the new type of information bot with the old type of human-helper bot. Instead of patterning Siri on a humanoid body, Apple used a human archetype -- the secretary or assistant. To do so, Apple gave Siri a voice and a set of skills that seem designed to make everyone feel like Don Draper. Siri listens to you and does what you say. 'Take this down, Siri... Remind me to buy Helena flowers!' And if early reviews are any indication, the disembodied robot could be the next big thing in how we interact with our computers."

If you didn't get Madrigal's "Dan Draper" reference, Draper is the leading character in AMC's highly acclaimed television series Mad Men. Kain writes that Siri's capabilities are "reminiscent of [IBM's] Watson's ability to quickly parse through enormous amounts of data on the quiz show." He asks, "How long before Watson is in our pocket, and Siri is just a thing of the past?" Both Kain and Madrigal agree that what makes both Siri and Watson possible is the availability of big data. John Stokes isn't particularly impressed with Siri's artificial intelligence (AI) credentials -- he calls the software "a chatterbot" -- but, he writes, "as Siri’s repertoire of canned responses grows, Apple could end up with a bona fide artificial intelligence, at least in the 'weak AI' sense. Siri may be yet another chatterbot, but it's a chatterbot with a cloud back-end, and that cloudy combination of real-time analytics and continuous deployment makes all the difference." ["With Siri, Apple Could Eventually Build A Real AI," Wired, 16 October 2011] Stokes writes that "Big Data" can result in "big smarts." He concludes:

"[Some critics may complain that what Siri does is] not really 'AI' because all Siri is doing is shuffling symbols around according to a fixed set of rules without 'understanding' any of the symbols themselves. But for the rest of us who don't care about the question of whether Siri has 'intentions' or an 'inner life,' the service will be a fully functional AI that can [respond] flawlessly and appropriately to a larger range of input than any one individual is likely to produce over the course of a typical interaction with it. At that point, a combination of massive amounts of data and a continuous deployment model will have achieved what clever [natural language processing] algorithms alone could not: a chatterbot that looks enough like a 'real AI' that we can actually call it an AI in the 'weak AI' sense of the term."

In another article, Kain agrees with Stokes that "the technology undergirding the software and iPhone hardware will continue to improve." ["Neuromancing the Cloud: How Siri Could Lead to Real Artificial Intelligence," Forbes, 17 October 2011] He also agrees that Siri "may not be the AI we had in mind, but it also probably won't be the final word in Artificial Intelligence either. Other companies, such as IBM, are working to develop ... 'cognitive computers' as well." As for the future, Kain writes:

"While the Singularity may indeed be far, far away, it's still exciting to see how some forms of A.I. may emerge at least in part through cloud-sourcing."

For readers unfamiliar with the term "singularity," it is a concept borrowed from science that describes an event horizon after which things change so much that no credible predictions can be made about the future. Inventor Ray Kurzweil believes that one such event horizon will take place the day computers become smarter than humans. He believes that this event horizon is just around the corner and wrote a book entitled The Singularity Is Near: When Humans Transcend Biology. To learn a little more about Kurzweil, read my post entitled Looking towards the Future with Ray Kurzweil. For a fuller explanation of the singularity, you can watch the attached video and hear it in Kurzweil's own words.

From Kain's comment above that "the Singularity may indeed be far, far away," it's clear that Kurzweil has his skeptics. Two such skeptics are Paul Allen, co-founder of Microsoft, and Mark Greaves, a computer scientist at Vulcan. They claim, "the singularity itself is a long way off." ["Paul Allen: The Singularity Isn't Near," Technology Review, 12 October 2011] Allen and Greaves explain:

"While we suppose this kind of singularity might one day occur, we don't think it is near. In fact, we think it will be a very long time coming. ... By working through a set of models and historical data, Kurzweil famously calculates that the singularity will arrive around 2045. This prediction seems to us quite far-fetched. Of course, we are aware that the history of science and technology is littered with people who confidently assert that some event can't happen, only to be later proven wrong—often in spectacular fashion. We acknowledge that it is possible but highly unlikely that Kurzweil will eventually be vindicated. An adult brain is a finite thing, so its basic workings can ultimately be known through sustained human effort. But if the singularity is to arrive by 2045, it will take unforeseeable and fundamentally unpredictable breakthroughs, and not because the Law of Accelerating Returns made it the inevitable result of a specific exponential rate of progress."

In other words, they are not at fundamental odds with Kurzweil they just believe that he is using "black box" thinking. Much of the magic that leads to the singularity (i.e., the "fundamentally unpredictable breakthroughs") take place in the "black box" and Allen and Greaves don't believe you can predict when the "black box" is going to be invented. They continue:

"Singularity proponents occasionally appeal to developments in artificial intelligence (AI) as a way to get around the slow rate of overall scientific progress in bottom-up, neuroscience-based approaches to cognition. It is true that AI has had great successes in duplicating certain isolated cognitive tasks, most recently with IBM's Watson system for Jeopardy! question answering. But when we step back, we can see that overall AI-based capabilities haven't been exponentially increasing either, at least when measured against the creation of a fully general human intelligence. While we have learned a great deal about how to build individual AI systems that do seemingly intelligent things, our systems have always remained brittle—their performance boundaries are rigidly set by their internal assumptions and defining algorithms, they cannot generalize, and they frequently give nonsensical answers outside of their specific focus areas. A computer program that plays excellent chess can't leverage its skill to play other games."

In my previous discussions about big data, I have mentioned this boundary issue, although not exactly using those terms. One reason we use an ontology at Enterra Solutions, is because it can make some of the relationship connections that systems like Watson can't. As Allen and Greaves explain below, even that approach has its limits. They write:

"Why has it proven so difficult for AI researchers to build human-like intelligence, even at a small scale? One answer involves the basic scientific framework that AI researchers use. As humans grow from infants to adults, they begin by acquiring a general knowledge about the world, and then continuously augment and refine this general knowledge with specific knowledge about different areas and contexts. AI researchers have typically tried to do the opposite: they have built systems with deep knowledge of narrow areas, and tried to create a more general capability by combining these systems. This strategy has not generally been successful, although Watson's performance on Jeopardy! indicates paths like this may yet have promise. The few attempts that have been made to directly create a large amount of general knowledge of the world, and then add the specialized knowledge of a domain (for example, the work of Cycorp), have also met with only limited success. And in any case, AI researchers are only just beginning to theorize about how to effectively model the complex phenomena that give human cognition its unique flexibility: uncertainty, contextual sensitivity, rules of thumb, self-reflection, and the flashes of insight that are essential to higher-level thought. Just as in neuroscience, the AI-based route to achieving singularity-level computer intelligence seems to require many more discoveries, some new Nobel-quality theories, and probably even whole new research approaches that are incommensurate with what we believe now. This kind of basic scientific progress doesn't happen on a reliable exponential growth curve. So although developments in AI might ultimately end up being the route to the singularity, again the complexity brake slows our rate of progress, and pushes the singularity considerably into the future."

Regardless of who is correct, for most of activities for which humans want to use artificial intelligence, being "somewhat intelligent," as Professor McCarthy put it, is probably good enough. And "good enough" gets better as more and more data becomes available and ways to access it improve.

November 07, 2011

Regional, Local, and Sustainable Sourcing

Steve Hall, Deputy Editor of Procurement Leaders Magazine, provocatively writes, "Collaboration is, for some, mostly pointless – we've all got our own goals and collaboration is just a moment when those goals overlap and little more. For others, it's a romantic notion in a pragmatic world." ["Sustainable Sourcing: Asking more of supplier relationships," Procurement Blog, 15 September 2011] I suspect that a lot of supply chain analysts would challenge Hall on those assertions. Most analysts would agree that supply chain stakeholders each have their own individual goals; but, they would argue, those goals overlap more than for "just a moment." Supply chains involve 24/7/365 activities. To function at peak performance, collaboration at the intersections of stakeholder interests must also be 24/7/365. That is a pragmatic, not a romantic, truth. Hall quickly reveals that he doesn't really believe those assertions himself; especially in the area of sustainable sourcing. He believes that when it comes to sustainable sourcing stakeholders must collaborate (continuously and pragmatically). He writes:

"Think of the relationship between a business and its suppliers. Procurement has got quite good at supplier relationship management – top functions are adept at segmenting suppliers and then opening the channels to improve either side of the deal, whether it be improving cash flow, fixing prices, sharing innovation. But when it comes to the sustainable standards that companies, particularly consumer facing ones, are looking to impose, the agenda naturally becomes one-sided. You want to work with us? Well, we have committed to reducing our footprint, which means you have to too. A hard-line makes sense, but the application of some of the collaborative methods that reap rewards in other aspects of purchasing is surely a more sophisticated way of going about achieving green targets."

I have noted in a number of previous posts that when it comes to supply chain sustainability, the only efforts that will last are those for which a business case can be made. For more on that topic, read my post entitled Supply Chain Sustainability. This is just as true in the area of sustainable sourcing as in any other area of of the supply chain. Hall writes about an interview he had with a Chief Procurement Officer (CPO) from a South American company. The CPO told Hall, "The supplier that brings good ideas for us and reduces costs and adds value to our sustainability measures, we give them credit." The CPO then asserted that, all else being equal, his company would choose the supplier with the best sustainability credentials. Based on this conversation, Hall concludes, "In that way, it's not only a supplier's emissions that need consideration, but their ability to collaborate that needs to inform sourcing decisions." He continues:

"Complicated yes, but when you consider that, in particular some of the more strategic suppliers that a purchasing organisation is going to work with can be vital to delivering stakeholder benefits, the potential of a supplier to help a business move towards its sustainable sourcing ideals should be built into the sourcing process. ... If a business is serious about sustainability, it needs to think seriously about what measures it needs to take to generate that kind of collaborative relationship with key suppliers. It’s taken a long time and a lot of external influence to get some companies to think that way about any kind of supplier relationship – and it may take a long time to get it right with sustainability – but those who are ahead are positioning themselves in the race for green credentials."

In another article on sustainable sourcing, Hall continues to press home the point that a business case must be made for sustainable efforts. If one can't be made, a company is likely engaging in what is commonly known as "greenwashing." Hall points out that the general public is already "cynical towards greenwashing efforts." ["Sustainable sourcing: investment trumps cheap cost-cutting," Procurement Blog, 1 April 2011] He writes, "You might argue that many businesses, particularly consumer-facing ones, get it already. Witness the fierce competition between Coca-Cola and Pepsi to produce the first renewable bottle (Pepsi claim to have won that)." Other businesses, he says, have been slower to understand the benefits of sustainable sourcing. That will probably change, he believes, once those companies understand the link between sustainability and cost savings. He explains:

"With commodity prices rising, and fuel costs in particular a threat that we've potentially not seen the worst of yet, does that perhaps mean that sustainability goes to the wayside? Well, I think the answer is that for some yes, for some absolutely not. We're already seeing prices being passed on to consumers and, of course, cost-cutting strategies coming to the fore, some of which you could argue have taken a rather short-term approach. ... Sustainable alternatives are the inverse of that. They require investment, research, collaboration – but they have long-term potential. Reducing packaging is an obvious way of doing this for food retailers, for example."

I've argued before that companies need to take the long view when it comes to strategy. At the same time, they need a few short-term wins along the way. When it comes to supply chain sustainability, the best place to look for short-term wins is waste reduction. Interestingly, waste reduction almost always leads to energy reduction as well. Hall reports that a study on the food industry concluded that it "is on track to reduce packaging weight by 19%, or 2.5 billion pounds, by 2020. That's the energy-saving equivalent of removing 363,000 homes or 815,000 gas-guzzlers." Hall admits that "going green isn't the answer to many of the problems that businesses face right now," but he believes that "the pressure on cost, particularly in areas such as fuel could be a catalyst for greater innovation."

Some manufacturers are reducing costs associated with transportation by moving manufacturing closer to demand centers. A related way to reduce such costs is to adopt regional or local sourcing strategies. John Shook, CEO of The Lean Institute, writes, "There is nothing inherently wrong with sourcing globally. But a single-minded focus on lowest piece-price with no regard to broader regional strategies leads to unneeded complexities." ["Time for Regional Sourcing Models?" Supply Chain Digest, 21 June 2011] He claims that, as global sourcing increased, "sensible considerations such as total cost, quality, logistics, and partnering for mutual prosperity ... disappeared." It sounds like there is a business case to be made for regional sourcing. Shook continues:

"'Outsourcing' grew along with 'offshoring,' under the edict, 'Match the price I can get in China or your contract goes up for bid.' And up for bid they did go, and out of business they went. First, smaller suppliers closed their doors, at huge cost to OEMs to replace the lost supply of parts and materials. They were followed by larger ones. ... As a result, supply chain logistics became increasingly complex. Other trends contributed: more sophisticated software and transportation systems, for example, led to the rise of '3PL' or third-party logistics specialists. Logistics and even supply chain strategy became outsourced. Outsourcing begat outsourcing. Not unlike the specter of machines designing machines (as in the Terminator), a monster was created. In the end, yet another key competence of manufacturers was lost to specialists whose interests were their own, not the OEM's. Certainly not the customer's. There is nothing inherently wrong with sourcing globally. But a single-minded focus on lowest piece-price with no regard to broader regional strategies leads to unneeded complexities."

To learn more about what other analysts are saying about simplifying supply chains, read my post entitled Reducing Supply Chain Complexity. Shook claims that "a new sourcing model is needed," one that is "regional and rational." He concludes:

"Anyone anywhere who wants to make his or her country a competitive manufacturing location needs to practice lean math. That's total cost -- including the potential cost of disruption on long-distance supply chains -- rather than the piece price plus slow freight cost calculation done by most manufacturing firms today. The USA, specifically, is already a much more 'competitive' manufacturing location than most senior managers seem to think, based on the continuing decisions to send manufacturing to locations far and wide."

Multinational corporations have started to adopt the regional/local sourcing strategy. Louise Lucas reports that "many companies [are] taking more direct control of supply chains across the globe. The aim is to ensure supply and quality, but also to remove some of the volatility from pricing; hence PepsiCo's decision to grow potatoes in China for its crisp brands and SABMiller's farming of barley in Africa for its beer." ["A market for local sourcing," Financial Times, 6 April 2011] In the end, the marketplace will determine which strategies win and which sustainable efforts endure. The good news is that "green" initiatives are no longer being pursued primarily for their public relations benefits.

November 04, 2011

The "Big Data" Dialogues, Part 7

In yesterday's post, one of the things I discussed was a study written by McKinsey consultants Brad Brown, Michael Chui, and James Manyika. ["Are you ready for the era of 'big data?" McKinsey Quarterly, October 2011] In that study, they ask "five big questions about big data" and I promised to discuss those questions in today's post. The questions concern "important ways big data could change competition: by transforming processes, altering corporate ecosystems, and facilitating innovation." As I noted yesterday, they don't claim to have all the answers and acknowledge that "these are still early days for big data, which is evolving as a business concept in tandem with the underlying technologies." Their first question involves a concept they call "radical transparency." They write:

"1. What happens in a world of radical transparency, with data widely available? -- As information becomes more readily accessible across sectors, it can threaten companies that have relied on proprietary data as a competitive asset. ... Cost and pricing data are becoming more accessible across a spectrum of industries. ... One big challenge is the fact that the mountains of data many companies are amassing often lurk in departmental 'silos,' such as R&D, engineering, manufacturing, or service operations—impeding timely exploitation. Information hoarding within business units also can be a problem: many financial institutions, for example, suffer from their own failure to share data among diverse lines of business, such as financial markets, money management, and lending. Often, that prevents these companies from forming a coherent view of individual customers or understanding links among financial markets."

Obviously, there is a lot to think about when it comes to radical transparency. Some of the consequences are going to make the business landscape more complex; however, the very big upside of transparency is that it will help break down internal corporate silos. For more on this subject, read my post entitled The Curse of Silo Thinking. Brown and company continue:

"Some manufacturers are attempting to pry open these departmental enclaves: they are integrating data from multiple systems, inviting collaboration among formerly walled-off functional units, and even seeking information from external suppliers and customers to cocreate products. ... More integrated data platforms now allow companies and their supply chain partners to collaborate during the design phase—a crucial determinant of final manufacturing costs."

Collaboration and transparency (or visibility) are both traits that will help define the best supply chains in the future. The next question asked by the McKinsey analysts deals with what I call "what if" exercises. They write:

"2. If you could test all of your decisions, how would that change the way you compete? -- Big data ushers in the possibility of a fundamentally different type of decision making. Using controlled experiments, companies can test hypotheses and analyze results to guide investment decisions and operational changes. In effect, experimentation can help managers distinguish causation from mere correlation, thus reducing the variability of outcomes while improving financial and product performance. ... Leading retailers ... are monitoring the in-store movements of customers, as well as how they interact with products. These retailers combine such rich data feeds with transaction records and conduct experiments to guide choices about which products to carry, where to place them, and how and when to adjust prices. Methods such as these helped one leading retailer to reduce the number of items it stocked by 17 percent, while raising the mix of higher-margin private-label goods—with no loss of market share."

As RFID technologies become more ubiquitous, even more data will be available and that information should offer further grist for experimentation. The next question involves personalization and customization.

"3. How would your business change if you used big data for widespread, real-time customization? -- Customer-facing companies have long used data to segment and target customers. Big data permits a major step beyond what until recently was considered state of the art, by making real-time personalization possible. A next-generation retailer will be able to track the behavior of individual customers from Internet click streams, update their preferences, and model their likely behavior in real time. They will then be able to recognize when customers are nearing a purchase decision and nudge the transaction to completion by bundling preferred products, offered with reward program savings. This real-time targeting, which would also leverage data from the retailer's multitier membership rewards program, will increase purchases of higher-margin products by its most valuable customers."

The McKinsey analysts aren't alone in their belief that personalization and customization are going to change the face of retailing. For more on this topic, read my post entitled Customization and the Supply Chain. One thing is for certain, customization will dramatically increase the complexity of some supply chains. The next question is a bit more controversial (at least the part concerning replacing management).

"4. How can big data augment or even replace management? -- Big data expands the operational space for algorithms and machine-mediated analysis. At some manufacturers, for example, algorithms analyze sensor data from production lines, creating self-regulating processes that cut waste, avoid costly (and sometimes dangerous) human interventions, and ultimately lift output. ... Products ranging from copiers to jet engines can now generate data streams that track their usage. Manufacturers can analyze the incoming data and, in some cases, automatically remedy software glitches or dispatch service representatives for repairs. Some enterprise computer hardware vendors are gathering and analyzing such data to schedule preemptive repairs before failures disrupt customers' operations. The data can also be used to implement product changes that prevent future problems or to provide customer use inputs that inform next-generation offerings."

Improving service is one obvious way that big data analysis can help companies gain customer loyalty. That's important because many analysts believe that customer loyalty is fading like other industrial age concepts. Improving customer service is not the only way that big data can help a company's bottom line. The McKinsey analysts report that "one global beverage company integrates daily weather forecast data from an outside partner into its demand and inventory-planning processes. By analyzing three data points—temperatures, rainfall levels, and the number of hours of sunshine on a given day—the company cut its inventory levels while improving its forecasting accuracy by about 5 percent in a key European market." As they conclude, "The bottom line is improved performance, better risk management, and the ability to unearth insights that would otherwise remain hidden." Their final question deals with future business models.

"5. Could you create a new business model based on data? -- Big data is spawning new categories of companies that embrace information-driven business models. Many of these businesses play intermediary roles in value chains where they find themselves generating valuable 'exhaust data' produced by business transactions. One transport company, for example, recognized that in the course of doing business, it was collecting vast amounts of information on global product shipments. Sensing opportunity, it created a unit that sells the data to supplement business and economic forecasts. Another global company learned so much from analyzing its own data as part of a manufacturing turnaround that it decided to create a business to do similar work for other firms. Now the company aggregates shop floor and supply chain data for a number of manufacturing customers and sells software tools to improve their performance. This service business now outperforms the company's manufacturing one."

Companies are starting to realize that their databases are tangible assets; but, they have to be careful how to use those assets. When MasterCard started talking to Madison Avenue, privacy advocates smelled blood in the air. The company quickly responded that its talks were preliminary. Nevertheless, it's inevitable that credit card companies are going to get into the big data analysis business. As noted yesterday, Forrester analysts believe that companies that can help make sense of big data have a bright future. Their McKinsey counterparts agree. Brown and company write:

"Big data also is turbocharging the ranks of data aggregators, which combine and analyze information from multiple sources to generate insights for clients. In health care, for example, a number of new entrants are integrating clinical, payment, public-health, and behavioral data to develop more robust illness profiles that help clients manage costs and improve treatments. And with pricing data proliferating on the Web and elsewhere, entrepreneurs are offering price comparison services that automatically compile information across millions of products. Such comparisons can be a disruptive force from a retailer's perspective but have created substantial value for consumers. Studies show that those who use the services save an average of 10 percent—a sizable shift in value."

Cliff Saran reports that a study entitled the "IBM Business Analytics and Optimization for the Intelligent Enterprise" asserts that "one in three business leaders frequently make decisions without the information they need and half don't have access to the information they need to do their jobs. That has significant competitive implications." ["What is big data and how can it be used to gain competitive advantage?" Computer Weekly, 1 August 2011] With the dawn of the big data era, those statistics should change significantly. Saran continues:

"According to McKinsey, the use of big data is becoming a key way for leading companies to outperform their peers. 'We estimate that a retailer embracing big data has the potential to increase its operating margin by more than 60%. We have seen leading retailers such as Tesco use big data to capture market share from local competitors, and many other examples abound in industries such as financial services and insurance, the report says."

As I've pointed out before, big data is not just for big businesses and Saran agrees. He writes:

"While it may seem that huge scientific projects, winning gameshows, and medical research fit in naturally with big data analytics, there is no reason why smaller organisations and those that are perhaps not at the cutting edge of IT cannot benefit. [Rebecca Wettemann, vice-president at Nucleus Research,] believes there is a huge opportunity in big data at smaller companies with cloud computing. 'One of the really interesting things is the ability for smaller businesses to access applications that are available in the cloud, particularly in marketing and e-commerce,' she says."

Hopefully, these dialogues will convince even the most skeptical of individuals that the Big Data Era is not only rapidly approaching but that its first waves have already washed across the corporate shore.

November 03, 2011

The "Big Data" Dialogues, Part 6

Steve Lohr, technology columnist for the New York Times, writes: "The quest to find decision-making insights in the modern data flood is certainly an appealing notion. After all, there is so much of data, from the traditional stuff inside corporate databases to e-mail, Web-browsing patterns, social-network messages and sensor data. Information drives decisions, so more of it ought to open the door to better decisions. The World Economic Forum has declared that data is a new asset class. All that is the intellectual and marketing tailwind behind the concept known as big data." ["Big Data: Sorting Reality From the Hype," 30 September 2011] In both his headline and opening paragraph, you can sense Lohr's skepticism. As President and CEO of a company that is, in fact, trying "to find decision-making insights in the modern data flood," I have to pay attention to what the skeptics are thinking.

The source of Lohr's skepticism was a Forrester study that had just been released. Lohr reports that the study "provides some leavening perspective on the big data phenomenon." It turns out, however, that the authors of the study conclude, "that big data is a real and significant trend." They write: "Big data technology, while early-stage, is not vapor-ware." Vaporware is a pejorative term that describes computer hardware or software that is announced to the general public but never actually materializes. The "leavening perspective" to which Lohr refers deals with the fact that a lack of talent to deal with big data is holding back many companies. As a result, he writes, "big data is an applied science project in most companies." He reports that "the major potential constraint is not the cost of the computing technology but the skilled people needed to carry out these projects — the data scientists." As anyone in the industry knows, finding good programmers who can deal with big data remains a challenge. Lohr concludes:

"Big data is about finding patterns in the proverbial noise of vast, unstructured data sets. The big data tools, [Boris Evelson, a Forrester analyst and coauthor of the report, with Brian Hopkins,] noted, are not themselves costly. Much of the software is based on open-source Hadoop, a framework for handling diverse data and probing it with distributed, parallel-processing computing clusters. There are commercial versions from companies including Cloudera, I.B.M., EMC and Hortonworks. And business intelligence software makers, like Microstrategy, are integrating their offerings with big data tools. And there are cloud-based services emerging for big data applications. Yet if the tools are comparatively low-cost, the skills needed are specialized and technical. Exploring for patterns in the data is not yet for the corporate rank and file. 'In big data today,' Mr. Evelson said, 'it's all about programming. You need Java programmers, computational statisticians and mathematicians."

To that list of skilled workers, I would add ontologists. As I explained in Part 4 of these Big Data Dialogues, Enterra's approach to big data uses a unique ontology that can help identity relationships in ways that other approaches can't. Forrester analysts believe that the future of start-up big data firms is very bright. In fact, "Forrester expects that by Q3 2012, companies such as Teradata, Oracle, SAP/Sybase, Microsoft and HP/Vertica will acquire Hadoop start-ups such as Cloudera, MapR Technologies, DataStax, HStreaming and Outerthought." ["Forrester predicts data warehouse suppliers will integrate Hadoop big data platform," by Cliff Saran, Computer Weekly, 17 October 2011]

McKinsey consultants Brad Brown, Michael Chui, and James Manyika believe that the business sector is about to enter the "Big Data Era." They assert that "radical customization, constant experimentation, and novel business models will be new hallmarks of competition as companies capture and analyze huge volumes of data." ["Are you ready for the era of 'big data?" McKinsey Quarterly, October 2011] They begin their report with case study of a company that was losing business to a competitor. The reason, it turns out, was that the competitor had embraced big data technology. Brown, et al. write:

"By constantly testing, bundling, synthesizing, and making information instantly available across the organization—from the store floor to the CFO's office—the rival company had become a different, far nimbler type of business. What this executive team had witnessed first hand was the game-changing effects of big data. Of course, data characterized the information age from the start. It underpins processes that manage employees; it helps to track purchases and sales; and it offers clues about how customers will behave."

Brown and his colleagues explain why big data is important. They write:

"Over the last few years, the volume of data has exploded. In 15 of the US economy's 17 sectors, companies with more than 1,000 employees store, on average, over 235 terabytes of data—more data than is contained in the US Library of Congress. Reams of data still flow from financial transactions and customer interactions but also cascade in at unparalleled rates from new devices and multiple points along the value chain. Just think about what could be happening at your own company right now: sensors embedded in process machinery may be collecting operations data, while marketers scan social media or use location data from smartphones to understand teens' buying quirks. Data exchanges may be networking your supply chain partners, and employees could be swapping best practices on corporate wikis. All of this new information is laden with implications for leaders and their enterprises. Emerging academic research suggests that companies that use data and business analytics to guide decision making are more productive and experience higher returns on equity than competitors that don't."

That kind of argument helps ease the skepticism that Lohr expressed at the beginning of this post. Whereas Lohr writes that increased access to information "ought to open the door to better decisions," the McKinsey analysts confirm that it does. They go on to report that their own research shows "that 'networked organizations' can gain an edge by opening information conduits internally and by engaging customers and suppliers strategically through Web-based exchanges of information." They continue:

"Over time, we believe big data may well become a new type of corporate asset that will cut across business units and function much as a powerful brand does, representing a key basis for competition. If that's right, companies need to start thinking in earnest about whether they are organized to exploit big data's potential and to manage the threats it can pose. Success will demand not only new skills but also new perspectives on how the era of big data could evolve—the widening circle of management practices it may affect and the foundation it represents for new, potentially disruptive business models."

Normally, the word "disruptive" causes chills to run up the spines of supply chain professionals. In this case, however, being disruptive is a good thing because it promises a better future. Saul Klein, an entrepreneur and a partner in a private equity firm, asserts that "successful disruptive businesses" deliver not only good service and a quality product but "something that is fundamentally better than what is already available." ["Ask the experts: Make yourself disruptive," Financial Times, 26 April 2011] That is what big data technologies promise to deliver -- something that is fundamentally better than what is already available.

Brown and company go on to ask "five big questions about big data." (We'll discuss those questions in tomorrow's post.) The questions concern "important ways big data could change competition: by transforming processes, altering corporate ecosystems, and facilitating innovation." They don't claim to have all the answers, after all, they acknowledge, "these are still early days for big data, which is evolving as a business concept in tandem with the underlying technologies." Before asking the first of their five questions, they identify what they believe are "big data's key elements": "First, companies can now collect data across business units and, increasingly, even from partners and customers. ... Second, a flexible infrastructure can integrate information and scale up effectively to meet the surge. Finally, experiments, algorithms, and analytics can make sense of all this information." Like past waves of technology that have ushered in new eras, Brown and company believe "the era of big data also could yield new management principles." The reason is simple, "future competitive benefits may accrue to companies that can not only capture more and better data but also use that data effectively at scale."

How big are those benefits? "A study from IBM shows that companies which excel at finance efficiency and have more mature business analytics and optimisation can experience 20 times more profit growth and 30% higher return on invested capital." ["What is big data and how can it be used to gain competitive advantage?" by Cliff Saran, Computer Weekly, 1 August 2011]

If you're still skeptical about the world being on the cusp of the big data era, you should listen to the prediction that Sanjay Mirchandani, chief information officer at EMC, made to Saran. He told Saran that he "believes there is a perfect storm" gathering that will be "driven by affordable IT and the ability to gather information." "The onus on IT," he says, "is to leverage data." Saran concludes:

"Experts agree that big data offers a big opportunity for businesses. The technology appears relatively immature and the idea of a complete big data solution is a bit of a pipedream. There are products that can handle aspects of big data, like analysis of large datacentres, but this is not the complete story - businesses should begin to pilot big data projects to evaluate how to benefit from the additional insight it can potentially offer."

The fact that Saran reports that "the technology appears relatively immature" should instill excitement rather than skepticism. There are already some pretty amazing things being done with big data and, if Saran is correct, we've only begun to understand its potential.