Leadership and strategy in the news

Citation

Henry, C. (2017), "Leadership and strategy in the news", Strategy & Leadership, Vol. 45 No. 6, pp. 58-63. https://doi.org/10.1108/SL-09-2017-0087

Of strategies and leadership

Getting vision right

When new behavior and new ways of thinking are required, an essential step is for the CEO, the board, and key managers to have an image in their minds of what the organization will look and act like after achieving its strategic goals.

When CEOs say they’ve defined their company’s vision, I ask them to explain it to me. Many respond with something like, “Our vision is to be the most innovative, agile company in our industry.” To which I reply, “That’s a mission, not a vision.”

In cases like these, the so-called vision merely repeats what is already in the strategy, and, worse, does nothing to emotionally engage the people who are being asked to implement it. A leader’s vision – particularly if that leader needs to bring about significant change in the organization – should start as a vivid, credible image of an ideal future state. The clearer a CEO is about what people should do differently to achieve new, challenging objectives, the greater his or her chances of achieving the changes necessary for success. New behavior doesn’t come from missions, however aspirational, but from deep, emotional commitment to doing things differently.

The following five principles will help guide a leader with a new strategy to make sure that the key people who are necessary to successfully implement it are operating from the same idea of what success will look like. The upshot should be a common vision of what will be seen, heard, and felt when necessary improvements are in place.

1. Find your own unique way. There is no simple, generic way to craft a real vision, one that is a powerful asset for change. It must be tailored to the character of the company.

2. Appeal to emotions often and vividly. As important as anything else, a description of the optimal organization must paint a picture that people are drawn to because it strikes them as more satisfying than today’s environment.

3. Describe changes that can be imagined. For the leader seeking to implement a new strategy, a carefully crafted vision is the best way to acknowledge the extent of the changes that will be necessary, particularly when those changes affect popular, long-standing practices.

4. Describe valued behavior, not values.

5. Be both firm and flexible. A leader who is formulating a vision must be firm about core elements of what should be in it but can and should be flexible on others.

Dan Ciampa, “What CEOs Get Wrong About Vision and How to Get It Right,” Sloan Management Review, August 2017.

Is near-shoring about to replace off-shoring?

In today’s globalized world of business, the ever-increasing requirements of customers regarding products and services has led to a new trend - nearshoring, which allows the companies to respond to customer needs with shorter delivery times and greater flexibility. Miebach Consulting has conducted an international study on this topic to determine how supply chains are affected by current and future shoring strategies, to evaluate the factors for shoring decisions and to show what shoring trends companies expect in the future.

One of the main conclusions of the study is that an increasing amount of companies (51 percent of the participants) are producing in closer proximity to their markets instead of moving the production abroad. The study also shows that this percentage is going to increase even more, since 26 percent of the participating companies believe that nearshoring is a trend that is going to have a very high or high relevance in a near future, above the offshoring and the onshoring or local production (22 percent and 17 percent, respectively).

“Miebach’s Nearshoring Study Shows that Production is Being Relocated Closer to the Industrialized Countries,” Miebach Consulting, 29 June 2017, www.miebach.com/en/publications/

Technology and disruption

Rethinking digital transformation

Digital transformation is not about technology. A key misconception about digital transformation is that it is something that companies choose to do with technology or is primarily about their implementation and use of technology. It isn’t.

Instead, digital transformation is about how technology changes the conditions under which business is done, in ways that change the expectations of customers, partners, and employees.

For example, the rise of new disruptive businesses like Uber Technologies Inc. and Lyft Inc. resulted in large part from changes in the technological infrastructure that were not initiated by the company’s founders. Instead, these startups recognized that the widespread adoption of personal mobile devices equipped with certain features provided new opportunities to bring people together to exchange goods and services. They responded to these opportunities by developing novel services that catered to changing customer (and driver) expectations. The success of these platforms further changed business conditions, creating even more new opportunities. For instance, the New York-based restaurant technology company Mobo Systems Inc., doing business as Olo, is building upon the Uber platform to offer restaurant delivery that relies on Uber drivers as delivery people.

Likewise, many of the most significant technological changes to the competitive environment your company faces lie outside your control, but they are created by a pervasive digital infrastructure that continues to evolve. The key question of digital transformation is whether you are paying close enough attention to these changes to respond to the resulting changes in expectations of customers, partners, and employees for how business is done – or whether a competitor or a startup will respond first?

Digital transformation is not a process that will ever be complete, at least not in the near future. New classes of technologies – artificial intelligence, blockchain, autonomous vehicles, augmented and virtual reality – will likely become widely adopted over the coming decade or two, fundamentally changing expectations yet again. By the time you adapt to today’s digital environment, that environment will have likely already changed significantly.

Therefore, digital transformation is better thought of as continual adaptation to a constantly changing environment. The need for transformation won’t abate, even if you successfully transform. It involves ongoing scanning of the environment to recognize evolving trends, continual experimentation to determine how to effectively respond to those trends, and then propagating successful experiments across the company.

Gerald C. Kane, “Digital Transformation’ is a Misnomer,” Improvisations, 7 August 2017, http://sloanreview.mit.edu/article/digital-transformation-is-a-misnomer/

When Big Data goes bad

Society and businesses have fallen in love with big data. Stoking this appetite is the sheer growth in the volume, velocity, and variety of the data.

Most of all, many business leaders see high potential in a fourth “V”: value. Given our ability to access and (potentially) understand every move our current and potential customers make, coupled with access to their demographic, biographic, and psychographic data, it seems logical that we should be able to form a more intimate, meaningful relationship with them. Every data point should move the business at least one step closer to the customer.

Yet despite all the digital breadcrumbs, it turns out that marketers might know less about individual consumers than they think. The numbers don’t lie – or do they? What if much of this data is less accurate than we expect it to be?

Perils ranging from minor embarrassments to complete customer alienation may await businesses that increasingly depend on big data to guide business decisions and pursue microsegmentation and micro-targeting marketing strategies. Specifically, overconfidence in the accuracy of both original and purchased data can lead to a false sense of security that can compromise these efforts to such an extent that it undermines the overall strategy.

John Lucker, Susan K. Hoggan, and Trevor Bischoff, “Predictably Inaccurate: The Prevalence and Perils of Big Data,” Deloitte Review, 31 July 2017, https://dupress.deloitte.com/content/dam/dup-us-en/articles/3924_Predictably-inaccurate/DUP_Predictably-inaccurate-reprint.pdf

Regulating risk in the era of Big Data

Certainly the complexity of these AI-powered algorithms and how they are designed increases the risks. Sophisticated technology such as sensors and predictive analytics and the volume of data that is readily available makes the algorithms inherently more complex. What’s more, the design of the algorithms is not as transparent. They can be created “inside the black box,” and this can open the algorithm up to intentional or unintentional biases. If the design is not apparent, monitoring is more difficult.

And as machine learning algorithms become more powerful – and more pervasive – financial institutions will assign more and more responsibility to these algorithms, compounding the risks even further.

Governance of these algorithms is not as strong as it needs to be. For example, while rules such as SR11-7 Guidance on Model Risk Management describe how models should be validated, these rules do not cover machine learning algorithms. With predictive models, you build the model, test it, and it’s done. You don’t test to see if the algorithm changes based on the data you feed it. In machine learning, the algorithms change, evolve and grow; new biases could potentially be added.

We just don’t see regulators talking about the risks of machine learning models, and they really should be paying more attention. For example, in loan decisioning, the data could inform an unconscious bias against minorities that could expose the bank to regulatory scrutiny.

“The Rise of Machine Learning and the Risks of AI-Powered Algorithms,” The Financial Brand, 23 August 2017, https://thefinancialbrand.com/67008/machine-learning-artificial-intelligence-regulation-compliance-risks/

Getting the most from marketing technologies

Marketing leaders today do more than acknowledge that customer lifetime value matters; they actually focus their spending and staff resources accordingly. A Bain & Company survey of roughly 500 companies found that marketing leaders exhibit a few characteristics that set them apart from the bottom 25 percent of companies. The leaders are:

• 3.5 times more likely to embed employees in marketing who specifically focus on understanding the customer’s end-to-end experience;

• 1.9 times more likely to align their strategy with customer needs rather than channel needs; and

• 1.9 times more likely to scrutinize customer lifetime value in addition to more traditional last-touch metrics such as ROI, customer acquisition cost and click-through rate.

Applying a lifetime value lens also helps to identify the individual customers who merit the highest and lowest levels of investment. For years, a major clothing retailer had considered all customers as essentially having equal potential, and it spread its marketing dollars too thin. By turning a value lens on its department, channel and demographic data, the company learned that women whose first purchase was a handbag frequently returned to buy goods in other departments. Women who started through lower-priced, more impulse-based departments rarely returned. Likewise, first-time shoppers who then shopped in a new channel such as online had a higher lifetime value than those who shopped only in a single channel. Armed with this new knowledge, the retailer steered its marketing communications to women with the highest potential value, and realized a threefold annual increase in its return on spending for three years running.

Laura Beaudin, Brian Dennehy, and John Grudnowski, “Customer Lifetime Value: A Better Compass to Guide Your Marketing Automation,” Bain Brief, 2 August 2017, www.bain.com/publications/articles/customer-lifetime-value.aspx

When technology meets demography

According to the United States Department of Health and Human Services, individuals over the age of 65 will make up nearly a quarter of the population by the year 2040. Many older people will manage multiple chronic diseases, as more than 90 percent of people over 65 report at least one chronic condition.

Here are just a few of the many new technologies that are affecting long term services and supports now and/or are expected to do so in the future:

Robotic care: Japan has many robots that can serve as companions or home assistants for older adults. Paro the robot seal has been shown to calm people with Alzheimer’s disease. Honda’s Asimo autonomous robot can perform mundane tasks such as getting an older person some food or turning lights on and off. Panasonic’s Resyone carebot has gained recognition for being the first robot to meet ISO service robots standards; however, it doesn’t look much like a robot. It is in fact a device that can change shape, turning into a bed, chair and electric wheelchair as needed.

New uses for information technology: Honor Technology and HomeHero Inc. use information technology to match caregivers with those in need of care. Both companies have created complex algorithms that are regularly updated to make sure that any full- or part-time caregiver is a good match for the person in need of care. Factors taken into account include a caregiver’s schedule, languages spoken, skills and personality. Honor has an Uber-like program for family members and children of older parents who need to call in a short-term caregiver on short notice.

Smart homes: Instead of having a robot handle daily tasks such as cooking, cleaning and shopping, an older adult could count on various devices in the home to take care of jobs that he or she can no longer do alone. For example, a smart refrigerator could sense when there is not enough food and order items from a local grocery store or supermarket. An app connected to a door lock system could make it easy for an elderly person to let in a family member or trusted caregiver without having to get up and open the door.

“How Technology Will Impact Aging Now and the Near Future,” USC Leonard Davis School of Gerontology, http://gerontology.usc.edu/resources/articles/how-technology-will-impact-aging-now-and-the-near-future/

Industry focus

Remanufacturing versus the linear economic model

Is remanufacturing the new recycling? Petar Ostojic certainly thinks so. As CEO of Neptuno Pumps, a $13 million Chilean company that makes industrial equipment for the mining industry, he’s become a leading spokesman for what’s known as the circular economy: in which manufacturers reclaim old products, reengineer them to brand-new status, and resell to customers in a continual, virtuous cycle.

Headquartered in Chile’s Atacama Desert – which is not only the driest place on earth but also a world-renowned mining locale – the company again rebooted its factory a decade ago to cast pipes for mining. But as the bottom dropped out of the commodities market and customers suddenly became cost conscious, the company revisited its business model once again in 2015. The challenge: to make their products cheaper, more efficient, customizable, and higher tech in a world that is turning to seawater rather than fresh water as a key component of operations.

Today’s circular economy model calls for Neptuno to make, sell, or lease then repair used equipment it resells to customers, a clear departure from the old “use and discard” practices common in the mining industry. The company touts clear advantages in this approach: Customers still get a one-year guarantee (the same that Neptuno issues for new products), but pumps are 60-70 percent of the cost of new products and can be delivered in a much shorter time frame.

Neptuno has rejiggered its design processes to make its pumps easier to disassemble and provide easier access to the equipment’s most expensive parts. It also works with customers to actively source material that it can recycle. And, going forward, it expects to build more local manufacturing capability to stay closer to its recycling suppliers.

The Ellen MacArthur Foundation forecasts that European manufacturers could save $630 billion a year in material costs by adopting a circular model. The circular economy, notes Ostojic, could be particularly beneficial for fast-growing emerging markets, where development cash is scarce and the time and logistics needed to deliver heavy-duty solutions to remote locations is precious.

“3 Work-Arounds for Your Business,” Chazen Global Insights (Columbia Business School), 28 August 2017, www8.gsb.columbia.edu/articles/chazen-global-insights/3-work-arounds-your-business

Innovation and tired brands

When Sarah Robb O’Hagan agreed to take over Gatorade in 2008, she thought she was assuming leadership of an iconic brand that had grown a little tired. What she found was something worse – a product in clear decline. Gatorade – a company that invented the sports drink category in the 1960s, and now a division of PepsiCo – was facing increasing competition, particularly by the lower-cost Powerade, a Coca-Cola product. Gatorade had seen a sales drop of 10 percent, while Powerade’s sales had grown 13 percent.

In response, Gatorade had tried to maintain growth by spinning out new flavors and expanding into new channels. It leveraged the distribution networks of PepsiCo, and had developed a wide range of new flavors and low- and no-calorie versions of the drink. But adding new product variants quickly hits a point of diminishing returns. For Gatorade, 2007 was the year it hit those limits.

What were the Gatorade team’s options? New versions, new flavors, or new channels didn’t offer much hope for growth. And truly disruptive innovations weren’t an option either, at least in the short term.

To find a solution, Sarah and her team reconnected with Gatorade’s core customer, the serious athlete. What they found was that these athletes did much more than just hydrate during athletic events. They would load up with carbohydrates before (Gold-medal winning runner Usain Bolt ate Skittles candy), and drink protein shakes after to recover. The team saw an opportunity to expand beyond the hydration niche, and introduced the G-Series family of products. The G-Series family included three complementary products to help athletes: energy chews and carbohydrate drinks to “Prime” before an athletic event; the core hydration drink to help the customer “Perform”; and protein shakes and bars to “Recover” after an event.

Growth restarted almost immediately. Despite fewer flavors and less discounting of prices, sales of the drink rose dramatically. From a low of less than $4.5 billion in 2009, Gatorade hit $5.6 billion in sales in 2015, and owned 78 percent of the US market. Powerade’s growth stopped. In 2015 it had $1.3 billion in sales, about 19 percent of the US market.

David Robertson, “How Gatorade Invented New Products by Revisiting Old Ones,” Harvard Business Review 17 August 2017.

Beyond outsourcing: flash organizations

At first glance, the organization chart for the maker of True Story, a card game and mobile app in which players trade stories from their daily lives, resembled that of any company. There was a content division to churn out copy for game cards; graphic designers to devise the logo and the packaging; developers to build the mobile app and the website. There was even a play-testing division to catch potential hiccups.

Upon closer inspection, the producer of True Story wasn’t really a firm: The workers were all freelancers who typically had never met and the entire organization existed solely to create the game and then disbanded.

True Story was a case study in what two Stanford professors call “flash organizations” – ephemeral setups to execute a single, complex project in ways traditionally associated with corporations, nonprofit groups or governments.

The professors, Melissa Valentine and Michael Bernstein, contend that information technology has made the flash organization a suddenly viable form across a number of industries. And, in fact, intermediaries are already springing up across industries like software and pharmaceuticals to assemble such organizations.

In principle, many companies would find it more cost-effective to increase staff members as needed than to maintain a permanent presence. The reason they do not, economists have long argued, is that the mechanics of hiring, training and monitoring workers separately for each project can be prohibitively expensive.

But Ms. Valentine, who studies management science, and Mr. Bernstein, a computer scientist, note that technology is sharply lowering these costs. “Computation, we think, has an opportunity to dramatically shift several costs in a way that traditional organizations haven’t realized,” Mr. Bernstein said. “It’s way easier to search for people, bargain and contract with them.

Noam Scheiber, “The Pop-Up Employer: Build a Team, Do the Job, Say Goodbye, New York Times 12 July 2017.

Culture and innovation

Abstract research drives most innovation

Pure research can often feel a million miles from anything fit for release onto the market, but is nonetheless a crucial part of the pipeline that underpins those innovations that are nearer to the market end of things.

A recent study set out to find a clear connection between pure scientific research and patentable inventions. The research looked at any connections that exist between every single patent issued between 1976 and 2015 by the US Patent and Trademark Office (of which there were around 4.8 million), and every single journal article published since WW2 (around 32 million). The researchers created a social network style map to connect up the two, by using the citations contained within each. This is crucial, because both papers and patents provide insights and references to the work upon which they’re based.

Intriguingly, they found a clear and constant flow between pure science and practical innovations. Whilst there are, of course, some papers that are rarely cited by future work, of those with at least one citation, a whopping 80 percent contributed to a future patent. Similarly, 61 percent of all patents referenced a research paper.

Equally, the innovations (patents) with the highest commercial impact, also had the highest amount of science behind them.

“Overall, our findings suggest that basic research matters. Scientific advances are not like the proverbial tree falling in the forest with no one around to hear. Rather, looking across the corpus of science, we find widespread connections to future patents – especially to the most valuable patents,” the authors say.

Adi Gaskell, “Linking Basic Research and Innovation,” Innovation Excellence, 21 August 2017, http://innovationexcellence.com/blog/2017/08/21/linking-basic-research-and-innovation/

Creativity, innovation, and stubbornness

One day in the summer of 2007, I flew over to Israel to meet with the local Texas Instruments team. After a few business meetings and a lecture I gave, one of the engineers asked to speak with me privately. Later that afternoon we met. He sought my advice. As it turned out, he was a very creative individual with many creative ideas. However, every time he presented his ideas to his management, they kept finding reasons not to implement them.

“Your ideas were killed not by management, but rather by you.” Do you think management failed to see the value that you saw in them? So what did you do about it?

I explained to him that management was highly unqualified to evaluate his ideas. He knew the technology much better than them, and they haven’t done any serious market study to know the value his ideas had with potential customers. If we let management determine the viability of new ideas, not only that we burden them with an overwhelming number of ideas to screen, but they run the risk of high rates of false positives and false negatives.

“So why was I the reason my ideas failed?” he wanted to know.

“Because you took no for an answer,” I explained to him. “You knew your ideas were good, and you let management stop you.”

Two years earlier, I stepped out of the office of a senior vice president in the company, after he refused to allocate resources to what I believed was going to be the next generation of connectivity technology: USB 3.0. I didn’t take no for an answer, and with the help of a few, highly qualified engineers, we’ve put together a prototype, presented it to Intel, and the rest is history. More than 4 billion USB 3 ports are shipped every year.

Yoram Soloman, Culture Starts with You, Not Your Boss (Large Scale Creativity, 2017).