Marina Gorbis's Blog, page 1351

Impact Investing Needs Millennials

As impact investing tries to make the move from philanthropic thought experiment to powerful instrument for global change, a vital demographic and financial reality is emerging — it’s going to be millennial investors (particularly those inheriting or building significant private wealth) who make or break it.

Since the term was coined in 2007, impact investing — the idea that private capital can be deployed to alleviate pressing social needs like access to clean water, affordable housing or preventative healthcare while returning a financial profit — has attracted significant public and media attention. However, impact investing’s legitimacy as an alternative asset class remains elusive.

Impact investment continues to suffer from limited transaction flow and anemic dollar commitments. Most relevant to stunted growth, however, is cultural resistance — the inertial apathy of traditional financial players who are wary of novel, risky investment structures and skeptical about trading some amount of profitability for social return. Without the commitment of commercial financiers to include impact investments in their core portfolios, or pressure from mainstream investors to insist that they do, impact investment’s route to scale is uncertain.

Enter the millennials (the roughly 80 million Americans born between 1980 and 2000, and their peers around the world), who conceive of financial return differently, and more expansively, than their elders. For millennials, pressing social problems are not just the preserve of philanthropists or governments. Millennials consistently cite social impact as one of the most important roles of business. Of all the generations alive today, millennials are the most willing to trade financial return for greater social impact, according to “Millennials and Money,” a 2014 study from Merrill Lynch’s Private Banking and Investment Group.

According to another study, U.S. Trust’s “Insights on Wealth and Worth,” wealthy millennials are almost twice as likely as their grandparents to regard their investments as a way to express social, political, or environmental values (see chart), and nearly three-quarters of millennials believe that it is possible to realize market-rate returns investing in companies based on their social or environmental impact.

These opinions matter. Millennials are poised to share in the largest intergenerational wealth transfer in human history — one widely-cited estimate puts its value at $41 trillion in the United States alone by the year 2052.

Millennials therefore represent a sizeable, well-capitalized cohort of investors with a generational commitment to furthering the social good and a desire to engage their peers — and parents — in doing likewise.  As recent events show, they are beginning to act on these principles. At the recent Nexus Global Summit on Innovative Philanthropy at the United Nations, which we attended, 600 largely millennial-aged participants from 41 countries representing nearly $750 billion in private and family wealth spent three days exploring and sharing case studies of social investments. Some of the investments had the sophisticated deal structures of large corporate transactions, some showed private sector engagement driving infrastructure development and quality-of-life improvement, and all demonstrated growing connections between policy and profit at national and international levels.

When we contrast our inspiring experience at Nexus alongside the still-limited impact- investment landscape, we conclude that three actions will be critical to accelerating the mobilization of capital by millennials and allowing impact investing to scale to a projected $1 trillion market by 2020.

First, private-sector entrepreneurs need to keep identifying opportunities to build companies that can accept and use impact capital to grow to scale, providing an increasing capacity for deal flow. Some commentators have compared the opportunity presented by impact investing to the early days of venture capital. We find such comparisons premature, but agree in one respect: to scale, impact investing will require a small contingent of ambitious investors prepared to make sizeable bets on promising entrepreneurs in order to demonstrate the asset class’s viability.

Second, millennials should vote with their wallets and demand that retail banks, wealth managers, and advisory firms provide a suite of financial products that range across the risk/return/impact triangle. Wealth management firms acknowledge that they are not yet positioned to give impact investing equal footing to conventional investments. In the “Millennials and Money” report we cited above, Merrill Lynch described one client’s impact investment as “a tricky undertaking for both client and advisor…the collaboration, in many ways an experiment, is ongoing.” For the same investment, the report asks, “what measures should be used to judge the social impact of these investments? How long should you wait for that impact to take hold, let alone a profit stream?” These are the questions investors are looking to advisory firms to answer, not just ask.

Of course, not all millennials will inherit or create millions in personal wealth. But our generation is remarkably consistent in attitude, regardless of financial position — 92% say business success should be based on more than profit. Millennials also believe in the power of private capital. More than half of millennials in the same study (conducted by Deloitte) believed that business, not government, will have the greatest impact in solving society’s most pressing challenges. We expect that wealthy millennials will pave the way for the mainstreaming of impact investment products for their peers as well as their Baby Boomer and Generation X parents and grandparents, whatever the size of their portfolios.

Third, growing impact investing will take collaboration and cooperation. Public- and private-sector actors will need to partner with academia to aggregate information on impact investing deal activity, compile best practices in impact measurement, reduce transaction costs, and inspire new participants through social engagement. The first report of the U.S. National Advisory Board on impact Investment is an important first step; the next challenge for government is to design and foster a supportive regulatory environment, one that regards private capital as positive force to be harnessed, and impact investors as partners in social progress.

We anticipate that millennials’ growing commitment to impact investing on multiple dimensions — dollars committed, deals completed, financial returns achieved, and development goals addressed.  Most importantly, however, we look forward to a growing alignment of developed world capital with a social conscience, driven by one of the core millennial mantras: doing well by doing good.

The Most Innovative Companies Don’t Worry About Consensus

Consensus is a powerful tool. When CEOs set out to conquer new markets or undertake billion-dollar acquisitions, we’d hope they’d at least sought out some consensus from their trusted advisors. We hope they’d be as sure as possible that their teams are ready, that their strategies are sound, and that they’d done their diligence.

The problem with consensus is that it’s expensive. And while it’s worth the cost of consensus in the pursuit big, bold moves, it’s often crushing to small experimental ones.

Consider the story of Nick. Nick is a typical manager at a one of the world’s most successful widget companies. He’s well respected, but far from the top of his organization. The good news for Nick’s company is that Nick has some great ideas; ideas for new ways of producing and distributing widgets that have never been thought of before. Nick’s company is also lucky that Nick has read The Lean Startup. Nick readily grasps the value in testing his ideas before asking for any full-scale operation.

Like a good student of the lean start-up, Nick plans out a cheap test for his latest idea, “Widget 2.0.” He determines that he can take just $10,000 to determine if Widget 2.0 has legs. If the test goes well, he’ll figure out the next step. If not, he’ll get back to his day job.

Inside most companies, this is where the problem kicks in.

Nick’s company is like most companies — only a small number of key executives have real authority to distribute cash and try new things. Everyone else is happy to defer responsibility (generally terrified of approving a failed experiment). But like most hierarchical organizations, Nick’s managers and their managers expect to be informed of his ideas before they make their way to the big boss. Even though there is only one check writer, there are a lot of potential naysayers. So Nick sets out to convince his key “stakeholders” to support his test plan for Widget 2.0. He has meeting after meeting and slowly gets people on board. Finally they approve his $10,000 dollar test.

The test fails, and Nick goes back to his day job. Success, right?

Not really.

In the last few decades executives have started to get wise about the value of systematically testing new ideas. Whether it was Rita McGrath explaining the importance of identifying risk in inherently risky ventures, Rosabeth Moss Kanter encouraging leaders to let their small experiments proliferate, or Eric Ries and Steve Blank teaching us the value of systematic experimentation and innovation accounting, the message has been clear: constantly testing new ideas is vital in the search for organic growth.

The reason testing is so vital is because it minimizes the investment required to eliminate uncertainty. In so doing, you increase the speed of innovation and decrease the cost of failure.

In the case of Widget 2.0, Nick’s company appeared to understand the value of his experiment… but their process got in the way. Consensus didn’t just slow Nick down, it dramatically increased the cost of his test. If Nick made $120,000 a year and he spent just a month trying to drive consensus around the project, the cost of his salary during the month of meetings doubled the cost of the experiment. If Nick had a small team working for him, seeking consensus may have quadrupled the cost of the experiment. And that’s not even accounting for the executives’ time that he had to sit down with.

Again, consensus can be a powerful tool. Consensus can be used to ensure multiple perspectives are looked at in any decision process. Consensus can help us honor fiduciary responsibilities. But it’s is slow, it’s messy, and it’s expensive. It eats away at the value of experimentation.

Milton Friedman once argued that the beauty of private capital is that it streamlines the act of experimentation in a capitalist society. Instead of driving consensus, “the market breaks the vicious circle [of having to convince a variety of stakeholders].” Individual entrepreneurs only need to persuade a few empowered parties that their ideas “can be financially successful; that the newspaper or magazine or book or other venture will be profitable.” To drive those same benefits inside our firms, consensus needs to be sought only where necessary.

So the challenge to managers is determining how to manage the consensus tax. How do you avoid investing in mediocre ideas, but still act with the speed and efficiency that helps you increase your ROI and get more at bats?

1. Acknowledge that not all investments are the same. Some investments are inherently complex and difficult to test systematically or at low cost. Often, these investments require that we drive consensus and be as sure as possible before we experiment. Others, however, are far less risky. If I can spend $10,000 for a one-day experiment that will tell me if a product won’t work in the future — that’s cheap. (That’s basically the same cost as the pro-rated salaries of a 100-person business unit on a 90-minute call.)

Managers in the modern organization need different processes for different types of investments. If your organization has one pathway for funding you’re doing it wrong. Either, you’re not considering the complex investments deeply enough or you’re crushing the small ones.

2. Push decision authority as low as possible. Senior executives are busy. As much as they want to control everything in the organization, it’s simply not realistic. To be nimble and innovative, part of the key is pushing decision authority as low as possible (but not lower).

What’s as low as possible? That’s going to change from situation to situation. But the key is acknowledging that the more senior you make your decision makers, the more waste you’ll require of those looking to experiment. It’s much better to have a slightly less qualified decision maker that is empowered to act on a much shorter timeline than to force decisions all the way to the top. If the latter is your approach, the only thing that will happen is your execs will end up drowning in a sea of meetings and nothing will ever get done.

To push decisions down, you need to limit your downside. Make sure that you hire smart people who you’d trust to make a good decision (not just order-takers). Make sure that you clearly define what success is for an experiment. And make your corporate mission and boundaries well known and well defined. If you do each of those things and distinguish between experimental investments and more meaningful operational investments, you’re already going to be in a good spot.

3. Don’t punish failure. Punish waste. Most executives are happy to point up the chain in order to avoid retribution. They’d rather not make a decision, because decisions can fail to pay off. It’s a lot easier to coordinate an additional meeting than to take the heat for another investment.

If you truly want to innovate, it’s important not to punish failure. Similarly, it’s not alright simply not to punish people at all. The type of punishment that I’ve seen work well is punishing waste; those who waste resources by failing twice the same way or those who waste time by being satisfied sitting in meeting after meeting without getting anything done. If you have an intrapreneur out there pushing the boundaries, learning new things, and adapting, you’re likely to have success in the future.

As Joe Bower once explained to me – “In pursuit of the novel, small is beautiful.” I’m more convinced than ever that he’s right. In part because small limits downside. But in part, because it also limits the need for consensus. In your search for innovation, it’s vital that you use consensus with some discretion. It’s a powerful tool, but it’s not for every occasion.

Integrate Analytics Across Your Entire Business

An Accenture survey conducted last year found that only one in five companies said that they were “very satisfied” with the returns they’ve received from analytics to date. One of the reasons analytics is working for the companies in this select group is because they tend to deploy analytics technologies and expertise across the breadth of the enterprise. But the survey also found that only 33% of businesses in the U.S. and Western Europe are aggressively adopting analytics across the entire enterprise. This percentage marks an almost four times increase in the trend of enterprise-wise adoption compared to a survey conducted three years earlier, but the question must still be asked — how can we improve this number?

Cross-functional analytics can be a challenge to implement for a variety of reasons including functional silos and a shortage in analytics talent. Yes, these obstacles can seem daunting at first, but our experiences tell us that they are not insurmountable. Following are tips organizations can follow to drive a horizontal focus on analytics and achieve their desired business outcomes, such as customer retention, product availability, or risk mitigation.

Identify the right metrics that “move the needle.” First, senior management should decide on the business goal for an analytics initiative and the key performance indicators to track that will put them on the right path toward success. For a high-performing retailer, we found that customer retention, product availability, labor scheduling, product assortment, and employee engagement were all leading indicators to driving growth and profitability for the company. Selecting the right critical metrics is a cornerstone of success as it brings focus and clarity on what matters most to the business.

Establish a center of gravity for analytics. Next, create an Analytics Center of Excellence (CoE) that spans the enterprise. A CoE is a team of data scientists, business analysts and domain experts from various business functions — sales, marketing, finance, and R&D, for example — that are brought together to facilitate a cross-pollination of experiences and ideas to find solutions to a variety of business goals. The CoE itself is organized into pods — generally made up of four to six people, with each person offering a different skillset — that are deployed across the business to solve problems that span multiple functions.

Develop a robust root cause analysis capability. Once CoE is created, the pod teams should perform root cause analyses to support the performance management process.  The retailer example mentioned above used root cause analysis to answer the question around what factors contributed to an unsuccessful marketing promotion. They tested hypotheses by asking questions such as: were results poor because of the marketing message, pricing and bundling, product availability, labor awareness of the promotion or did a competitor have an attention-grabbing marketing campaign happening at the same time? A successful CoE model provides a company with the capability to not only answer these questions with validated cross-functional insight, but also to determine the best decision around what to do next.

Make collaborative decisions. Using a CoE affords functional managers the ability to make collaborative and informed decisions. They are not left alone to develop root cause analysis insights in a vacuum. Rather, as a team, the managers and the CoE are able to make decisions and take actions based on the insights garnered together.  To accomplish this, it is critical to establish a forum with the cross-functional business leaders to share and visualize the data and interpret the insights for the purpose of decision making.

As an example, a consumer products company used a weekly executive management meeting as the forum to discuss the CoE’s insights and make decisions based on the outputs. In this instance, the head of the Analytics CoE was the facilitator of the meeting and focused the executives’ time on the decisions that needed to be made based on the important insights the data identified versus the noise that should be ignored (e.g. to better understand the effectiveness of a new product launch). The combination of data science, advanced visualization, and active decision making — along with an impartial facilitator with deep content expertise — was key to collaborative and effective decision making.

It’s important to note that once data-driven decisions are made and actions are set in motion, companies should track their progress against the metrics that were established at the start of their analytics journey. If goals are not being realized, they should repeat the process to understand the root causes of an issue that will help them achieve their business goals. In one instance, a bank’s Analytics CoE delivered such consistently positive results that the company formally branded all analysis coming out of the CoE so the business leaders could be aware of its quality and credibility outright. The branding encouraged business leaders to trust the insights and act on them faster.

When a company expands its analytics purview from functional to horizontal, it opens the door to greater opportunities and successes. While removing silos and taking a teaming approach to analytics is part of an internal virtuous cycle, another cycle is also created — the attained results are experienced by the customers and will keep them coming back for more.

Regular Exercise Is Part of Your Job

When we think about the value of exercise, we tend to focus on the physical benefits. Lower blood pressure, a healthier heart, a more attractive physique. But over the past decade, social scientists have quietly amassed compelling evidence suggesting that there is another, more immediate benefit of regular exercise: its impact on the way we think.

Studies indicate that our mental firepower is directly linked to our physical regimen. And nowhere are the implications more relevant than to our performance at work. Consider the following cognitive benefits, all of which you can expect as a result of incorporating regular exercise into your routine:

Improved concentration
Sharper memory
Faster learning
Prolonged mental stamina
Enhanced creativity
Lower stress

Exercise has also been show to elevate mood, which has serious implications for workplace performance.  I’m willing to bet that your job requires you to build interpersonal connections and foster collaborations. Within this context, feeling irritable is no longer simply an inconvenience. It can directly influence the degree to which you are successful.

There is also evidence suggesting that exercise during regular work hours may boost performance. Take, for example, the results of a Leeds Metropolitan University study, which examined the influence of daytime exercise among office workers with access to a company gym. Many of us would love the convenience of free weights or a yoga studio at the office. But does using these amenities actually make a difference?

Within the study, researchers had over 200 employees at a variety of companies self-report their performance on a daily basis. They then examined fluctuations within individual employees, comparing their output on days when they exercised to days when they didn’t.

Here’s what they found: On days when employees visited the gym, their experience at work changed. They reported managing their time more effectively, being more productive, and having smoother interactions with their colleagues. Just as important: They went home feeling more satisfied at the end of the day.

What prevents us from exercising more often? For many of us, the answer is simple: We don’t have the time. In fairness, this is a legitimate explanation. There are weeks when work is overwhelming and deadlines outside our control need to be met.

But let’s be clear: What we really mean when we say we don’t have time for an activity is that we don’t consider it a priority given the time we have available.

This is why the research illuminating the cognitive benefits of exercise is so compelling. Exercise enables us to soak in more information, work more efficiently, and be more productive.

And yet many of us continue to perceive it as a luxury; an activity we’d like to do if only we had more time.

Instead of viewing exercise as something we do for ourselves—a personal indulgence that takes us away from our work—it’s time we started considering physical activity as part of the work itself. The alternative, which involves processing information more slowly, forgetting more often, and getting easily frustrated, makes us less effective at our jobs and harder to get along with for our colleagues.

How do you successfully incorporate exercise into your routine? Here are a few research-based suggestions.

Identify a physical activity you actually like. There are many ways to work out other than boring yourself senseless on a treadmill. Find a physical activity you can look forward to doing, like tennis, swimming, dancing, softball, or even vigorously playing the drums. You are far more likely to stick with an activity if you genuinely enjoy doing it.

A series of recent studies also suggest that how we feel while exercising can influence the degree to which it ultimately benefits our health. When we view exercise as something we do for fun, we’re better at resisting unhealthy foods afterwards. But when the same physical activity is perceived as a chore, we have a much harder time saying no to fattening foods, presumably because we’ve used up all of our willpower exercising.

Invest in improving your performance. Instead of settling for “getting some exercise,” focus on mastering an activity instead. Mastery goals, which psychologists define as goals that center on achieving new levels of competence, have consistently been shown to predict persistence across a wide range of domains. So hire a coach, enroll in a class, and buy yourself the right clothing and equipment. The additional financial investment will increase your level of commitment, while the steady gains in performance will help sustain your interest over the long .

Become part of group, not a collective.  One recommendation aspiring gym-goers often receive is to find an exercise regimen that involves other people. It’s good advice. Socializing makes exercise more fun, which improves the chances that you’ll keep doing it. It’s also a lot harder to back out on a friend or a trainer than to persuade yourself that just one night off couldn’t hurt.

But there’s another layer to this research—one that is well worth considering before signing up for an exercise class this fall.

Studies indicate that not all “group” activities are equally effective at sustaining our interest.

We are far more likely to stick with an exercise regimen when others are dependent on our participation.

As an illustration, consider the standard yoga or pilates class. Each involves individual-based tasks that require you to work alone, albeit in the presence of others. Both activities technically take place within the context of a group, however in these cases the “group” is more accurately described as a collective.

Research suggests that if you’re looking to establish a routine that sticks, exercising as part of a collective is preferable to working out alone, but it’s not nearly as effective as exercising as part of a team. So consider volleyball, soccer, doubles tennis—any enjoyable, competence-enhancing activity in which your efforts contribute directly to a team’s success, and where if you don’t show up, others will suffer.

Regardless of how you go about incorporating exercise into your routine, reframing it as part of your job makes it a lot easier to make time for it. Remember, you’re not abandoning work. On the contrary: You’re ensuring that the hours you put in have value.

Being Bilingual Makes You Better at Non-Linguistic Tasks

In a small study, bilingual people were about a half second faster than monolinguals (3.5 versus 4 seconds) at executing novel instructions such as “add one to x, divide y by two, and sum the results,” say Andrea Stocco and Chantel S. Prat of the University of Washington. The findings are in line with past studies showing that children born into bilingual families exhibit superior performance on non-linguistic tasks. The experience of flexibly applying rules when speaking multiple languages may strengthen bilinguals’ executive functioning, the researchers say.

An Open Office Experiment That Actually Worked

Nowadays many people regard open-plan offices with skepticism — remnants of a once-cool work space fad that led to more distraction than innovation. As this article explains, there are downsides to too much transparency.

But we at The Bridgespan Group decided to test that conventional wisdom six months ago when we moved 70 employees from offices and cubicles on two floors of a building in Boston’s Back Bay to a dramatically different space fashioned out of the gutted top floor of a tower four blocks away.

It was a bid to tear down hierarchies and invigorate our already collaborative culture, and so far the experiment has been a success. The open layout has increased productivity, energy and connectedness. But the journey from a traditional office to this new space where everyone shares work benches, tables, lounge areas, and first-come-first-served private rooms took careful thought and planning.

The planning

Just over a year ago, 22 staff members — drawn from all roles and functions — gathered in our raw, unfinished new space for two and a half days to explore what to do with it. A team from Architects of Group Genius facilitated decision-making, joined by our building architects from CBT. Our challenge was to design a dramatically different kind of office that would enhance teamwork and insight around the projects at the heart of our work advising non-profit organizations. We also wanted to provide a much broader array of work space choices for all staff every day, yet keep costs down, befitting our own non-profit status (and budget!).

We broke into groups to think about the environments where we did our best work; we took field trips to spaces built for knowledge workers and created a spectrum of design schemes, from next-to-normal to radical. (A smaller group had already spent months researching design concepts, listening to TED talks on sound and space, and visiting innovative organizations.)

During the process, many of us thought back to the mid-summer week when the air conditioning system in half of our existing offices had suddenly failed. Forced to squeeze into the cooler space and share offices, cubicles and desks with colleagues, staff started working together in casual ways outside pre-planned meetings and appointments. Could we duplicate this happy accident in our new space? The literature told us that workers want personalization and choice. What if we achieved that not by offering a fixed office or cubicle, but by giving each staff member, at every level, many choices of where to sit and how to work every day, and within each day, as well as large flexible spaces for people to meet, brainstorm, and otherwise collaborate.

Photo credit: © Anton Grassl/Esto

The execution

At the end of our design lab, we handed off to our architects a “radical” plan which they built out over the next few months.

It included:

an open café, where staff bump into each other making coffee, or making sandwiches and catch up or take care of business
a “laboratory” space with tables, sofas and white boards at the heart of the office, where teams meet and discuss work previously done in closed conference rooms
a large, closed-off library space with lots of natural light that we call the “quiet car,” where people can work without interruption
several small comfortable seating clusters throughout the office for small-group conversations
a bank of small private rooms for people to use when they truly need privacy for meetings, phone calls, or individual work–but no private offices even for the most senior staff
sitting and standing work stations where people can park themselves day-to-day
glass-walled conference rooms so most meetings are seen by everyone, even if they aren’t heard
background noise masking, so that conversations in the open are heard as mild hubbub rather than distinct, distracting words
lockers in which staff can keep personal items

You can find more photos on this page of CBT’s website and at The Daily Muse.

Photo credit: © Anton Grassl/Esto

The results

Six months in, we continue to be amazed at how differently we work in the new space and how much the spirit of our office has changed. We used to make appointments to see each other; now, we often just run into each other, and all kinds of new ideas emerge from these unplanned collisions of two or three or four people.

Formal meetings are routinely held in the open areas, where it’s easy to bring in someone else on the spur of the moment—just because they’re passing nearby, or sitting in view.

We want our new space to remain dynamic, and keep improving. To that end, we created a “Way We Work” group, which holds regular community check-ins, and crafts new ways to solicit and act on feedback, including anonymous input. Our new office space is not so much built to last as built to change. And that spirit seems to be rubbing off on all of us who work in it.

 

How Thomson Reuters Is Creating a Culture of Innovation

It’s not easy for big companies to innovate. As Steve Blank, Clay Christensen, and many others have pointed out, once firms reach a certain size, most of their resources (and investment dollars) are rightly devoted to executing and defending their existing business model. Moreover, the skills that are cherished and rewarded for achieving current results differ from those that aid in discovery and experimentation, both of which are needed to drive innovation. As a result, fostering a true culture of innovation in big companies is often an aspiration rather than a reality.

If this is the case in your company, then it might be worthwhile to look at the experience of Thomson Reuters, a $12.5B global information solutions company. The company’s strategy of fueling growth through acquisitions served it well for many years – but this approach also reduced the focus on innovation. While many managers were developing new products and services for their own businesses, they were not leveraging innovation across the enterprise, and some were relying too much on acquisitions to drive both innovation and growth.

To reverse this, senior leadership took a number of steps. First they agreed to shift funding from small, incremental acquisitions to innovation. In early 2014, they established a “catalyst fund” – a pool of money that internal innovation teams could use for doing rapid proof of concept on new ideas. The fund was announced on the company’s internal website and teams from anywhere in the businesses were invited to submit their suggestions.

To access the fund, teams had to complete a simple two-page application about their idea, the potential market, and the value to the customer (what problem was being solved). The teams with the most compelling ideas were given an opportunity to present and defend their idea to the innovation investment committee, which included the CEO, CFO, and a few other senior executives. In the first month, five “winners” were announced and then immediately publicized on the Thomson Reuters internal web site. This triggered a great deal of interest, and a steady flow of applications.

The company also took a number of other steps, driven by a newly appointed executive sponsor and a full-time innovation leader, to make innovation a priority. Developed after talking with dozens of people both inside and outside the company, these steps included:

Building innovation metrics (such as number of ideas being considered, and amount of revenue from new products/services) into business unit operating reviews, so business leaders would pay attention to the pipeline and commercialization cycle time of new ideas.
Appointing “innovation champions” in every business – i.e., credible leaders who would help their business presidents implement programs and processes to move the needle on the innovation metrics. For example, the champions created a common terminology for innovation across the company so that everyone referred to the same types of innovation (e.g. product vs. operational) and referenced the same stages (e.g. “ideation” and “rapid prototyping”). They also built an online Thomson Reuters innovation “toolkit” that employees could use to educate themselves about innovation, run innovation events, and work through the process of translating ideas into commercial opportunities.
Creating an innovation “network” on the intranet site where internal entrepreneurs could share their stories and ideas, and get connected to others who were interested in solving customer problems in new ways.
Orchestrating a communications campaign with blogs, articles, and video interviews with internal innovators.
Organizing an “enterprise innovation workshop,” with representatives from every part of the business, to identify and plan ten specific innovations that leverage existing company assets – and implement them in 100 days or less.

In the spirit of innovation, all of these steps were initiated as experiments to focus on learning, adjusting, and figuring out what would work. For example, the innovation metrics were sharpened as the definitions of innovation evolved, and the experience of the first few innovation champions helped clarify criteria for selecting additional ones. Also, all of these steps were carried out with as much transparency as possible, so that all Thomson Reuters employees would not only know what was happening, but could contribute to the effort as well.

The results of all this work have been impressive. Innovation is now one of the hottest topics in the company. The innovation “network” is the most visited site on the company’s intranet, and more than 250 ideas were submitted by employees for consideration at the enterprise innovation workshop, some of which are already being implemented. Several Catalyst Fund projects, which span multiple business units, also are now being prototyped and piloted with customers and most of the businesses have a robust portfolio of innovative ideas that are moving through the pipeline. So although there is still much to be done, and the jury is still out, clearly the momentum for innovation is building.

There is no magic formula for how big companies can reinvent themselves. The innovators’ dilemma is still alive and well and is not easy to overcome. But the experience of Thomson Reuters shows that progress is possible – particularly if leaders use the lessons of innovation to build the innovation culture.

Technology Questions Every CMO Must Ask

Marketers today encounter a mind-boggling array of technologies. CMOs I talk to are swamped by meeting requests from technology vendors, and most feel an acute pressure to climb on the tech bandwagon. But they worry about the massive distraction of full-scale technology assessments—and about the risk of buying expensive tools that don’t live up to their potential.

My colleagues and I believe CMOs can make better technology sourcing decisions by asking five fundamental questions. The first two focus on avoiding the all-too-common trap of treating each technology decision in isolation.

1. Will the technology advance a critical marketing priority? This seems like an obvious consideration, but we often see the technology tail wagging the marketing dog. Plenty of the new tools have the potential to add value in an absolute sense, which is why they appear on CMOs’ radar screens in the first place. But the real question is how much value the tool under evaluation adds relative to other possibilities.

Marketers who ask this question make individual technology assessments in the context of the overall marketing priorities that a given tool will address. It’s hardly rocket science. But this common-sense discipline often falls victim to a combination of poor planning and siloed decision-making—for example, when individual marketing teams independently make narrow, channel-specific technology choices without accounting for interdependencies and appropriate sequencing.

2. Will the tool add balance to the marketing technology portfolio? It’s useful to categorize marketing technologies into three buckets. The first helps a company deliver more personalized marketing content and experiences to customers and prospects (especially through digital media). The second allows marketers to use data and analytics to reach better decisions. The third improves the effectiveness and efficiency of core marketing workflows. These buckets are interlinked. For example, marketing automation technology helps deliver personalized content and offers to large numbers of individual customers on a scale that would be unfeasible using traditional manual processes.

Over time, marketers should strive to build a technology portfolio that is balanced across the three buckets. So any individual technology assessment needs to account for how a given tool fits into the architecture of the overall portfolio.

In many ways, acquiring a new technology is the easy part. The harder part is getting people to use it—which raises three additional questions.

3. Is the organization culturally ready to adopt the new technology? Like technologies elsewhere, marketing technologies can unsettle long-held views and ways of working. Changing these attitudes and behaviors requires a multi-pronged approach: championing by senior leadership, evangelism by believers on the marketing front line, and active involvement of middle managers in encouraging the change. This “sponsorship spine” is at the core of effective change management and raises the odds of disciplined, deliberate adoption. Success requires identifying desired adoption behaviors, anticipating resistance and challenges, and having a deliberate mitigation plan — all before acquiring a new technology.

4. How readily can current marketing workflows integrate the new technology? To take one example: a number of new technologies can improve the analytic power of marketing test-and-learn processes. But many marketers still treat test-and-learn as an adjunct to their main creative and campaign-management workflows. If test-and-learn remains a sideshow, the impact of these new technologies on marketing outcomes will necessarily be limited. It’s only when core marketing processes are overhauled to integrate ongoing testing and iteration (so-called agile marketing) that the value of the new technologies will be realized.

5. Do potential users have the skills they need to benefit fully from the technology? Even when marketers are excited about a new tool, they may lack the skills and capabilities to use it. While most vendors do provide training and support, it may be inadequate to an organization’s needs. Additional training and other support—even new hires—may be required to bridge the capability gaps. Hence, the technology assessment needs to include a plan (and a budget) for whatever additional training and capability investments are needed.

Questions like these are part of the playbook of technology buyers in other parts of the enterprise, who have been adopting new technologies for more than two decades. Marketing is a relative newcomer to this game, which is why so many CMOs feel overwhelmed. The good news is that a well-planned technology diligence process—a process that anchors individual decisions in a larger context and focuses on creating the right environment in terms of sponsorship, process changes, and capabilities—can significantly improve the odds that marketing’s many new technologies will deliver on their promise.

When a Simple Rule of Thumb Beats a Fancy Algorithm

For a retailer, it’s extremely useful to know whether a customer will be back or has abandoned you for good. Starting in the late 1980s, academic researchers began to develop sophisticated predictive techniques to answer that question. The best-known is the Pareto/NBD (for negative binomial distribution) model, which takes a customer’s order history and sometimes other data points, then simulates whether and how much she will buy again.

Actual retailers, though, have tended to stick with simpler techniques, such as simply looking at how long it has been since a customer last bought anything, and picking a cutoff period (nine months, say) after which that customer is considered inactive.

This resistance to state-of-the-art statistical models has frustrated the academics. So, a decade ago, marketing professor Florian von Wangenheim (now at the ETH Zurich technical university in Switzerland) and his then-student Markus Wübben (now an executive at a tech incubator in Berlin) set out, in Wangenheim’s words, to “convince companies to use these models.”

To do this, Wübben and Wangenheim tested the predictive accuracy of Pareto/NBD and the related BG/NBD model against simpler methods like the “hiatus heuristic” — the academic term for looking at how long it’s been since a customer last bought anything — using data from an apparel retailer, a global airline, and the online CD retailer CDNow (from before it was acquired by Amazon in 2001). What they found surprised them. As they reported in a paper published in 2008, rule-of-thumb methods were generally as good or even slightly better at predicting individual customer behavior than sophisticated models.

This result wasn’t a fluke. “I’ve seen much more research in this area, many variables have been added to these models,” says Wangenheim. “The performance is slightly better, but it’s still not much.”

One way to look at this is that it’s just a matter of time. Sure, human beings, with “their limited computational abilities and their incomplete information,” as the great social scientist Herbert Simon put it, need to rely on the mental shortcuts and rules of thumb known as heuristics. But as the amount of data that retailers are able to collect grows and the predictive models keep improving, the models will inevitably become markedly better at predicting customer behavior than simple rules. Even Simon acknowledged that, as computers became more powerful and predictive models more sophisticated, heuristics might lose ground in business.

But there’s at least a possibility that, for some predictive tasks at least, less information will continue to be better than more. Gerd Gigerenzer, director at the Max Planck Institute for Human Development in Berlin, has been making the case for decades that heuristics often outperform statistical models. Lately he and others have been trying to define when exactly such outperformance is most likely to occur. This work is still ongoing, but in 2011 Gigerenzer and his colleague Wolfgang Gassmaier wrote that heuristics are likely to do well in an environment with moderate to high uncertainty and moderate to high redundancy (that is, the different data series available are correlated with each another).

Citing the Wübben/Wangenheim findings, Gigerenzer and Gassmaier (why so many of the people involved in this research are German is a question for another day), posited that there’s a lot of uncertainty over if and when a customer will buy again, while the time since last purchase tends to be closely correlated with every other available metric of past customer behavior. Ergo: heuristics win.

There are other areas where the heuristic advantage might be even greater. Financial markets are rife with uncertainty and correlation — and the correlations are strongest when the uncertainty is greatest (think of the parallel downward trajectories of lots of different asset classes during the financial crisis of 2008). Sure enough, while sophisticated financial models performed poorly during the recent financial crisis, simple market heuristics (buying stocks with low price-to-book-value ratios, for example) have withstood the test of time. Along those lines, Gigerenzer has been working with the Bank of England to come up with simpler rules for forecasting and regulating financial markets.

“In general, if you are in an uncertain world, make it simple,” Gigerenzer said when I interviewed him earlier this year. “If you are in a world that’s highly predictable, make it complex.” In other words, your fancy predictive analytics are probably going to work best on things that are already pretty predictable.

Does Your Sales Team Know Your Strategy?

Frank Cespedes, HBS professor and author of Aligning Strategy and Sales, explains how to get the front line on board. For more, read his article, Putting Sales at the Center of Strategy.

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