Snow Melts From the Edges
RGM Newsletter

https://mail.google.com/mail/u/0/?shva=1#label/BLOG/FMfcgxvzKQhBBqCRGJlgfSmBvlLQqMJF



This is an incredibly powerful metaphor: your markets/business can erode at the edges. Do you have the systems in place to detect and deal with it.Go to the article to see Rita McGrath's comments

Andy Grove, Intel’s fabled former CEO and author of Only the Paranoid Survive observed that “When spring comes, snow melts first at the periphery, because that is where it is most exposed”. For people running organizations, this has important ramifications – if snow melts from the edges, how do we make sure we see when this is happening? Below are some questions to ponder upon.

Do I have mechanisms to come in direct contact with the ‘edges’? 
Am I regularly gaining exposure to diverse perspectives?
 
Am I trusting and empowering small, agile teams?
 

Do I have mechanisms for fostering ‘little bets’?
  
Do I regularly get out of the building to see what’s going on?
  
Are incentives aligned with gaining uncomfortable news?

 
Am I making sure I’m not in denial?

 

 

Strategy for Start-ups
Joshua GansErin L. ScottScott Stern
HBR, May-June, 2018
https://hbr.org/2018/05/do-entrepreneurs-need-a-strategy#strategy-for-start-ups

This is a super article that I recommend you read in its entirety (HBR reprint R1803B)

The Entrepreneurial Strategy CompassStrategic opportunities for new ventures can be categorized along two dimensions: attitude toward incumbents (collaborate or compete?) and attitude toward the innovation (build a moat or storm a hill?). This produces four distinct strategies that will guide a venture’s decisions regarding customers, technologies, identity, and competitive space

A Short Guide to Strategy for Entrepreneurs
Kevin J. Boudreau
OCTOBER 17, 2017

https://hbr.org/2017/10/a-short-guide-to-strategy-for-entrepreneurs

Very similar to our model

Strategy is hard work, and there are no magic shortcuts. What is offered here is a starting point: the most basic questions that every successful business must answer. Entrepreneurs who design their business around these questions will have a leg up when it comes to crafting strategy:

What Value Are You Intending to Create, and for Whom?Customers buy products and services because they perceive value in them. The first step toward a successful strategy is to clarify how you plan to create value, and for whom. That means defining who your customers are
How Do You Plan to Deliver That Value?In plotting your position in the market, defining how you’ll create value and for whom, you also need to define your operating model. The operating model is the set of choices and practices defining how to carry out the business. This will typically imply a set of trade-offs in trying to find a combination of activities that allows you to stake out your position — delivering certain dimensions of your solution better than the competition.
What Is Your Competitive Advantage — Your Sources of Uniqueness?The last question on the index card is perhaps the central question of strategy: Why won’t you be copied? Even if you’re delivering a great product that customers love and making money doing it, if competitors can easily enter the market and copy you, economic theory suggests they’ll drive your profits down to zero

Why the Lean Start-Up Changes Everything
Steve Blank

https://hbr.org/2013/05/why-the-lean-start-up-changes-everything

Incredible article. Two  concepts have been the literature for a while—Lean Startups and Design Thinking. They are fundamentally based on creating, rapidly testing and validating concepts. If we look at the Market Driven Growth model (MDG), we basically show how to do this from concept creation, concept validation, resourcing (often ignored in other discussions), and then execution. Leadership Framing, critical in MDG is again often ignored in discussions of these processes. .

Going forward, I will be sharing some tools that have not been incorporated into our Kellogg class but I think our valuable

Launching a new enterprise—whether it’s a tech start-up, a small business, or an initiative within a large corporation—has always been a hit-or-miss proposition. According to the decades-old formula, you write a business plan, pitch it to investors, assemble a team, introduce a product, and start selling as hard as you can. And somewhere in this sequence of events, you’ll probably suffer a fatal setback. The odds are not with you: As new research by Harvard Business School’s Shikhar Ghosh shows, 75% of all start-ups fail. 

But recently an important countervailing force has emerged, one that can make the process of starting a company less risky. It’s a methodology called the “lean start-up,” and it favors experimentation over elaborate planning, customer feedback over intuition, and iterative design over traditional “big design up front” development. Although the methodology is just a few years old, its concepts—such as “minimum viable product” and “pivoting”—have quickly taken root in the start-up world, and business schools have already begun adapting their curricula to teach them continually learn from customers. 

One of the critical differences is that while existing companies execute a business model, start-ups look for one. This distinction is at the heart of the lean start-up approach. It shapes the lean definition of a start-up: a temporary organization designed to search for a repeatable and scalable business mode. 

After decades of watching thousands of start-ups follow this standard regimen, we’ve now learned at least three things:1. Business plans rarely survive first contact with customers. As the boxer Mike Tyson once said about his opponents’ prefight strategies: “Everybody has a plan until they get punched in the mouth.”2. No one besides venture capitalists and the late Soviet Union requires five-year plans to forecast complete unknowns. These plans are generally fiction, and dreaming them up is almost always a waste of time.3. Start-ups are not smaller versions of large companies. They do not unfold in accordance with master plans. The ones that ultimately succeed go quickly from failure to failure, all the while adapting, iterating on, and improving their initial ideas as they continually learn from customers.

The lean method has three key principles:

First, rather than engaging in months of planning and research, entrepreneurs accept that all they have on day one is a series of untested hypotheses—basically, good guesses. So instead of writing an intricate business plan, founders summarize their hypotheses in a framework called a business model canvas 

Second, lean start-ups use a “get out of the building” approach called customer development to test their hypotheses. They go out and ask potential users, purchasers, and partners for feedback on all elements of the business model, including product features, pricing, distribution channels, and affordable customer acquisition strategies. The emphasis is on nimbleness and speed: New ventures rapidly assemble minimum viable products and immediately elicit customer feedback. 

Third, lean start-ups practice something called agile development, which originated in the software industry. Agile development works hand-in-hand with customer development. Unlike typical yearlong product development cycles that presuppose knowledge of customers’ problems and product needs, agile development eliminates wasted time and resources by developing the product iteratively and incrementally. It’s the process by which start-ups create the minimum viable products they test.

The founders of lean start-ups don’t begin with a business plan; they begin with the search for a business model. Only after quick rounds of experimentation and feedback reveal a model that works do lean founders focus on execution

WHY MARKETING ANALYTICS HASN’T LIVED UP TO ITS PROMISE


Carl F. Mela
Christine Moorman

https://hbr.org/2018/05/why-marketing-analytics-hasnt-lived-up-to-its-promise


A very important topic and really worth going to the article for greater insight

We see a paradox in two important analytics trends. The most recent results from The CMO Survey conducted by Duke University’s Fuqua School of Business and sponsored by Deloitte LLP and the American Marketing Association reports that the percentage of marketing budgets companies plan to allocate to analytics over the next three years will increase from 5.8% to 17.3%—a whopping 198% increase. These increases are expected despite the fact that top marketers report that the effect of analytics on company-wide performance remains modest, with an average performance score of 4.1 on a seven-point scale, where 1=not at all effective and 7=highly effective. More importantly, this performance impact has shown little increase over the last five years, when it was rated 3.8 on the same scale. 

How can it be that firms have not seen any increase in how analytics contribute to company performance, but are nonetheless planning to increase spending so dramatically? Based on our work with member companies at the Marketing Science Institute, two competing forces explain this discrepancy—the data used in analytics and the analyst talent producing it. We discuss how each force has inhibited organizations from realizing the full potential of marketing analytics and offer specific prescriptions to better align analytics outcomes with increased spending.

The Data ChallengeData are becoming ubiquitous, so at first blush it would appear that analytics should be able to deliver on its promise of value creation. However, data grows on its own terms, and this growth is often driven by IT investments, rather than by coherent marketing goals. As a result, data libraries often look like the proverbial cluttered closet, where it is hard to separate the insights from the junk. 

In most companies, data is not integrated. Data collected by different systems is disjointed, lacking variables to match the data, and using different coding schemes……..What’s more, most companies have huge amounts of data, making it hard to process in a timely manner. Merging data across a vast number of customers and interactions involves “translating” code, systems, and dictionaries. Once cohered, vast amounts of information can overwhelm processing power and algorithms. Many approaches exist to scale analytics, but collecting data that cannot be analyzed is inefficient.An irony of having too much data is that you often have too little information 

The Data Analyst ChallengeThe CMO Survey also found that only 1.9% of marketing leaders reported that their companies have the right talent to leverage marketing analytics. Good data analysts, like good data, are hard to find. Sadly, the overall rating on a seven-point scale, where 1 is “does not have the right talent” and 7 is “has the right talent,” has not changed between the first time the question was asked in 2013 (Mean 3.4, SD =1.7) and 2017 (Mean 3.7, SD =1.7)… 

……In light of the exponential growth in customer, competitor, and marketplace information, companies face an unprecedented opportunity to delight their customers by delivering the right products and services to the right people at the right time and the right format, location, devices, and channels. Realizing that potential, however, requires a proactive and strategic approach to marketing analytics. Companies need to invest in the right mix of data, systems, and people to realize these gains

Liberate Your Team with Clearer Processes
Elizabeth Doty

https://www.strategy-business.com/blog/Liberate-Your-Team-with-Clearer-Processes?gko=b4eb7&utm_source=itw&utm_medium=20180522&utm_campaign=resp

The age old debate/feeling about process---could not have explained it any better:

Effective processes are not about adding red tape — they are about enabling “flow.”

Ask the members of any team if they want to institute better processes, and be prepared for them to roll their eyes. “‘Better processes’ means ‘more bureaucracy,’” someone will mutter. But ask that same team how much they enjoy doing projects the hard way — duplicating efforts, scrambling to meet deadlines when someone drops the ball, or bearing the brunt of customer fury — and you can expect the floodgates to open.Why do people love to hate “process” but rail against disorganization? It is because most people associate processes with checklists, forms, and rules — the overseer breathing down their necks. Not surprisingly, leaders wanting to foster innovation and creativity are reluctant to institute such rigid controls and procedures. 

In one sense, this aversion to processes is justified. Historically, formal procedures have been used to maintain control, not to simplify work. Process engineers can get carried away with forms and spreadsheets. However, a culture of “winging it” can be just as frustrating. In their 2011 book, The Progress Principle: Using Small Wins to Ignite Joy, Engagement, and Creativity at Work, Harvard professor Teresa Amabile and developmental psychologist Steven Kramer show that employees are least motivated on days when they face setbacks that inhibit their work. And sociologist Randy Hodson has found that coherent production processes are a key driver of trust in management. Hassles, exceptions, and “gotchas” increase stress, sap the feeling of progress, and force your team to fight the same fires over and over. Even worse, winging it tends to erode safety and quality, and increase the risk of ethical drift. 

At their heart, effective processes are not about adding red tape — they are about enabling “flow.” According to management thinker Eli M. Goldratt, the real innovation behind Ford’s production lines, the Toyota Production System, and “lean” production is the shift from managing resource efficiencies in isolation to managing the flow of value generated by a system. Wherever there is an activity that happens repeatedly in your business, there is a potential flow. As a leader, you have the choice to leave this flow to chance, to control it, or to channel it. 

At their heart, effective processes are not about adding red tape — they are about enabling “flow.” 

Think of a river. If the banks are not strong and defined, the river dissipates across the countryside and has little force. This is like the operation in which employees are given little guidance, and whose efforts meander or collide. Another river may have locks that strictly regulate how much water can flow when and where. This is a company that tries to control every step every employee takes every day. The entire system is rigid and slow, because management can never keep up with the exceptions and re-prioritizations, and employees’ time is consumed by filling out forms and following procedures.

By contrast, a company with effective processes is like a river with strong banks. People’s attention and energy are channeled where they will have the most impact. The work environment, habits, tools, and methods guide people into doing things right the first time, based on a continually evolving set of shared best practices. No locks are required: Instead, employees are liberated to focus their creativity on developing new best practices, delighting customers, noticing changes in the competitive landscape, or tackling their company’s next moon shot. 

Designing processes this way involves looking at how work naturally gets done and where simple structures can increase the throughput of value — much the way Japanese gardeners will design the paths in a garden after seeing where people walk. There are several approaches that incorporate this idea of flow, including Goldratt’s “theory of constraints” (and its project-based counterpart, “critical chain”), agile project management, and lean production’s “pull-based” scheduling. Whatever method you choose, here are three core ideas that I’ve found lead to the biggest breakthroughs:• Make sure everyone sees the big picture. When people focus on efficiency in one part of a process, they suboptimize the system as whole — because they don’t weigh the impact of their actions on downstream groups or on the customer. To improve the flow, ensure everyone understands how their work fits together and how to prevent downstream defects through clearer handoffs, giving other departments sufficient lead time, and prioritizing based on overall goals. 

• Love your bottlenecks. As Goldratt has shown, every flow has a capacity constraint — a “Herbie.” Instead of blaming your bottleneck, treat it as scarce resource whose capacity should never ever be wasted. Does it receive top-quality inputs from other groups? Is it ever left idle? Do you squander capacity by constantly switching priorities? A meta-analysis of Goldratt’s methods found companies reduced lead times by 75 percent and improved on-time performance by 50 percent. 

• Do the right things more reliably. As management theorists W. Edwards Deming and Joseph Juran have shown, variability kills quality. Your team may produce excellent work most of the time, but if it is inconsistent, people will be forced to waste time checking to ensure no one drops the ball. Did you call the client with the update? Should I? You can reduce workload and increase the psychological experience of flow by identifying a few best practices and making them into solid habits. 

What flows do you need to master in your business? Launching apps? Integrating mergers? Hiring and retaining employees? Select one that will increase your firm’s competitive advantage, set a goal, and then support your team in using one of the methods above. Don’t wait until the fires are out — firefighting is a symptom of poor processes. Instead, dedicate small chunks of time to improvement, chipping away at the biggest time wasters first. A Pareto chart can help you rank problems by frequency or cost. Wherever possible, listen to your team and adopt their recommendations, but insist on rapid feedback so they learn which solutions work. In the end, working on processes in a collaborative way is one of the fastest, most effective vehicles for building engagement and translating values into action.

Four Business Models for the Digital Age
John Sviokla

https://www.strategy-business.com/blog/Four-Business-Models-for-the-Digital-Age?gko=67c74&utm_source=itw&utm_medium=20180417&utm_campaign=resp

Start thinking the future

Digitization, which is of course happening all around us, is opening up a whole new spectrum of opportunities to create value. But how do you navigate this new horizontal world? 

Opportunities for companies in every industry are occurring on two critical dimensions: knowledge of the end customer and business design, i.e., breadth of product and service offerings. These dimensions combine to form four business models for creating value (see exhibit): Suppliers, Multichannel Businesses, Modular Producers, and Ecosystem Drivers. 

Suppliers, in the lower left quadrant, have little direct knowledge of the preferences of their end customers, and may or may not have a direct relationship with them. These companies sell their products and services to distributors in the value chain. Due to the ease of digital search, they are vulnerable to pricing pressures and commoditization as customers look for less expensive alternatives. Washing-machine manufacturers are a good example of Suppliers, as are companies that create mutual funds sold by someone else. 

If you are a Supplier, you need to make sure your operations are as efficient as possible, but that’s only the first step. As digitization continues, end customers will increasingly expect you to cater to their likes and needs. So if you don’t know much about your end customers and aren’t intent on solving their problems, you’ll need to find other ways to ward off commoditization. That means making sure that your product is highly differentiated or that it goes through a distribution channel other than one controlled by an Ecosystem Driver, another of the business models, which has a broad supply base. Otherwise, you risk losing all the value your enterprise has created 

Haier, the world’s largest manufacturer of white goods, has deployed various strategies to differentiate itself from competitors. It has developed a variety of niche products, including washing machines that accommodate the long gowns worn by women in Pakistan, and freezers that can keep food frozen for 30 hours in the event of a power outage in Nigeria. More recently, Haier used the Internet to open up its innovation process to people outside the company, enabling an unprecedented level of customization. 

Multichannel Businesses, in the upper left quadrant, have deep knowledge of their consumers because they enjoy a direct relationship with them. Companies in this category provide access to their products in various digital and physical channels to ensure the seamless experience their end customers have come to expect. Many banks and brokerage houses are Multichannel Businesses, as are some retailers and insurance companies. 

If you are an Multichannel Business, there’s no such thing as too much customer knowledge. Broadening your understanding your customers’ life-event needs is essential for building out the integrated experience that will retain existing consumers and attract new ones. 

IKEA, the world’s largest furniture company, is an example of an Multichannel Business that continues to find ways to enhance the range of offerings within its value chain. Building upon its global presence — currently more than 300 stores in 41 countries — IKEA used its extensive knowledge of its customers (gleaned through visits to homes, for example) to develop “products for an everyday life” — from bedroom furniture to prepared food, all under IKEA’s iconic brand. After decades of focus on the customer experience in its stores, IKEA recently launched online shopping, making the purchasing experience truly seamless and gaining a way to learn even more about its customers.Modular Producers, in the lower right quadrant, offer a distinct capability that spans the ecosystem, but they have little direct knowledge of the end customer. Their plug-and-play offerings can work with any number of channels or partners, but they rely on others for distribution as well as for guidance on what the customer needs. A good example is payment companies that enable the consumer to pay for a wide range of goods and services, such as groceries and college tuition. 

If you are a Modular Producer, you need to be the best at everything. As is the case with Suppliers, competition is fierce, so your offerings need to be innovative and well priced.Square Inc. fits the profile of a Modular Producer. Founded in 2009, the B2B payments company has continuously launched innovative software and hardware products that are ecosystem-agnostic. Square’s point-of-sale, payroll, employee management, and appointment apps can be used on Apple and Android devices alike, as can its chip and magstrip readers. 

Ecosystem Drivers, in the upper right quadrant, have the best of both worlds: deep end-customer knowledge and a broad supply base. They leverage these dimensions to provide consumers with a seamless experience, selling not only their own proprietary products and services but also those from providers across the entire ecosystem. Thus, they create value for themselves while extracting rent from others. Large internet retailers in the U.S. and China are good examples of Ecosystem Drivers, as are some healthcare providers. 

If you are an Ecosystem Driver, you’ll want to keep pushing the boundaries in both dimensions, increasing your knowledge of end customers and the breadth of offerings available to them… 

…research demonstrates, the prospects for creating value are greatest for companies that participate in ecosystems rather than in value chains, so Ecosystem Drivers have the greatest potential for value creation and Suppliers the smallest. All four paths are viable routes to enduring success, provided you are clear on what your generic strategy is and what that strategy requires. If, however, you are losing customers or growing more slowly than your market, you should consider moving to a different quadrant, either by expanding your knowledge of your end customers or by becoming more of an ecosystem.Or even by doing both: GE is moving from being a Supplier of industrial products to an Ecosystem Driver in the Industrial Internet of Things, with the help of Predix, the cloud-based operating system it launched last year. Serving as a platform for services provided by third-party vendors as well as GE business units, Predix helps companies collect, analyze, and leverage operational data so they can optimize the performance of their entire system. As Predix’s customer base grows, so will GE’s status as an Ecosystem Driver. 

As digital becomes the new normal, the paths to success are there for the taking. But be sure you know your destination before setting out.

Exploring the Rich Tapestry within the Three Horizon Framework

Posted on August 22, 2016 by @paul4innovating

https://paul4innovating.com/2016/08/22/exploring-the-rich-tapestry-within-the-three-horizon-framework/

Very interesting discussion on the Three Horizon model we deploy and teach on our Market Driven Growth process at Kellogg.

Within our ‘business as usual’ attitudes, there actually lies the seeds of destruction. Today there is a relentless pace; we are facing stagnation in many maturing markets if we don’t evolve.Yet we actually subvert the future to prolong the life of the existing. We need to frame our innovation needs differently for exploring and exploiting innovation across different time horizons to move beyond the usual.
 Commonality within innovation is becoming increasingly important. We need to build clear common languages of innovation, frameworks, methods and approaches.There is a pressing need to frame innovation in different ways, to meet change that lies in the future. We are in need to clarify our options and this requires multiple thinking horizons to work through to deliver a richer tapestry of innovation discovery.Innovation is constantly facing disruption; it is constantly going through life cycles and new waves of different activities and we begin decay faster today than ever. We run an increasing risk that we begin to lose any dominance or competitive position increasingly. We need to innovate to sustain ourselves and maintain our market positions in a rapidly evolving world. 

The key requires us to manage this transition, not let others manage it for us. We need a far more robust, well thought-through way to apply our innovation resources to meet and anticipate these changing events. It is how we manage this transition becomes so critical. 

The three horizon framework needs to become the innovation space for dialogues, planning, portfolio debates, differentiating the distinctions between the three time line perspectives and generally arguing for inclusion, the value and importance of the thinking and then applying the appropriate resources needed in the management of innovation across these three different timelines.The 3H framework is a powerful enabler.The value of the weak signals needs amplifyingWe need to exploit developing trends that are emerging in the different but future horizons and begin to tune in and discover the emerging possible options in the future.The discussions in any forecasting or futuristic planning often have conflicting views of the future, compared to the existing realities based on those products and services that are providing the returns for today’s business. Yet the future is also equally rooted in the present, often called ‘weak signals’I am a great follower of Dave Snowden’s thinking and work over at www.cognitive-edge.com on “making sense of complexity in order to act” which includes SenseMaker® and the Cynefin Framework, which I have written upon in its value, in this post “use of the Cynefin model for innovation” ,and within his work equally are clear views of managing change. 

Dave Snowden’s has a view that works for me in applying the thinking around the three horizons, this fits so well. He argues instead of trying to tackle the unknowable, as it is inherently unknowable, he rightly suggests 1) we fully explore the evolutionary potential of the present, 2) bring in as wide an engagement of views to find a more sustainable or resilient set of solutions to emerge and 3) in his view, and most probably the most important point, it is how you build the narrative and descriptors, as the danger becomes the more you attempt to predict and evaluate, the more you can close down options, some far too early. 

He suggests the more you can hold onto this descriptive level, the longer you have in widening the range of intervention points as more knowledge becomes available. You spend less time on (predicting) outcomes and more time on measuring vectors (velocity, acceleration, magnitude, force of direction) which for me, allows the progressive build of the right future capabilities, in more evolving and evolutionary ways of learning from exploring and experimenting, the key transition point of Horizon 2 (h2). 

Resisting the early decision.It is often the cases we can detect change but we consciously ignore it or dismiss it out of hand. This is often the place where the disruptor is presently at work, both existing or new competitors, exploring or exploiting different options, working at displacing your products and market positions. The combinations of new technologies, concepts and business models are constantly emerging and we need to be pioneers these as well as detect them as they emerge, anticipating the change these might bring and focus on building the capacity and capabilities to advance on your own curve of understanding.We need to separate and structure different mindsets to developing innovation capabilities to explore and prepare for the future, as well as deepen the exploration, to leverage the present. Structuring the approach, by looking across multiple horizons, allow you to evolve the entire innovation portfolio and begin to recognise the many gaps that exist within your thinking, within your capabilities and capacities to innovate.Separating the horizon lenses 

By looking at this through separate horizon lenses does equally assist you in allocating the appropriate but usually different resources that are needed to be applied, to each of the time horizons and challenges that are identified and lie within them.The three horizon framework has the clear intent to grow awareness and offer a better understanding of how innovation works and fits, with also its great value for clarifying the structuring and allocation of innovation’s management. It can be used for portfolio alignment, resource structuring and the mechanism for broad dialogue of explaining decisions and describing the growing consensus of the future direction.The three horizon framework  can offer a vital part within all the organisations thinking around working through its innovation ambitions, not just for the present but for the future and how these can transition, connecting the reality of the present with the concepts of the future.The need is we all should make the case that different types of innovation operate and evolve over different time horizons and need thinking through differently.The three horizon framework  goes well beyond simply a planning tool, it does provide a valuable evolutionary perspective that dialogues can be formed around, so decisions on where to focus and what resources need to be applied can be made for delivering a constantly evolving ‘state’ of innovation development. Dialogues that deliver that then get translated into more plausible and coherent set of activities, projected into the future, searching for emerging winners that can change and challenge your existing business.The three horizon framework is about having strategic conversations about the future, that feeds the discussions about your innovation direction, shaping the longer-term portfolio and capability understandings. It is increasingly vital to understand all of its ways to contribute to your innovation developments and needs.Its value – if well-managed – can offer a helpful way for a significant series of dialogues and tensions to surface, but through this engagement and respect for different positions, you can find mutual ways of connecting your innovation activities and resolve these different opinions, emerging over the different horizons and diverse thinking. You are managing uncertainty in better ways, as a team or organisation through this framing dialogue.If you would like to explore all the different ways that give the three horizons framework a much richer return in its value and use, then let me know.

Decision making in your organization: Cutting through the clutter
At the root of any good decision is categorizing what kind of decision needs to be made, by whom, and how quickly.

https://www.mckinsey.com/business-functions/organization/our-insights/decision-making-in-your-organization-cutting-through-the-clutter

Great discussion on the process of decision making. Go to the site for a full discussion including a podcast

The decision-making process should be a choice, where you have a level of commitment that drives action. If the commitment and action isn’t there, then something’s wrong in the decision process, itself…. 

…. The other thing that we’ve observed is some best practices around decision making are situational. For some types of decisions, those best practices work brilliantly, and for other types of decisions, they’re terrible. If you don’t apply the right best practices in the right way at the right time, you can get things that don’t work. It’s not enough to say, “I have experience, and I know what makes a good decision.” You have to say, “What am I optimizing for?” With decisions that can be quickly undone, you should take a lot more risk in making a wrong decision, because you can undo it. Decisions where the stakes are high and you can’t undo them need to be a lot more thoughtful and carefully planned 

.... we’ve found that it’s helpful to talk about four different kinds of decisions. 

One is your classic big-bet decision, where you’re making a decision that’s going to have enormous implications for the company. It’s often not easy to undo it. It might be an acquisition or a merger. It might be a major capital investment. That’s the first type. 

The second type is a decision that isn’t actually a single decision. We call it a cross-organizational or a cross-functional decision, where many different parts of the organization are involved and there are lots of little decisions that accumulate to a larger decision. A good example of this might be something like pricing or decisions in a supply chain. 

The third type of decision is one that can easily be delegated to a particular role—somebody who has enough knowledge to make a good decision, may interact with other people to get feedback and perspective on making the decision—but does not need to be made in a committee and does not need to be drawn out. It does not need a carefully mapped decision process. 

 There is a fourth type, ad hoc decisions, which are decisions that are infrequent and reasonably small and contained, where you don’t try to figure it out or map it out ahead of time. You just say, well there’s a bunch of stuff that might bubble up, and we’ll deal with it as it comes up. We’ll cross that bridge when we come to it.

 

How to turn marketing efficiency into growth

Those who participated in our Kellogg program will recognize the challenge we raised in the Danaka case.

At Western Union, fueling growth starts with taking a hard look at how effective current marketing programs are. Chief Strategy, Product and Marketing Officer Libby Chambers explains how it’s done.

Growth leaders are adept at finding money to invest in initiatives that drive revenue. In this interview, Libby Chambers, Western Union’s chief strategy, product and marketing officer since 2015, talks with McKinsey’s Barr Seitz about how she has focused on ratcheting up marketing effectiveness and efficiency to release funds for growth programs.

Thinking like an investor

The investing metaphor is apt in that you’ve got many different places where you can spend your money—countries, channels, products, and customer groups. You almost have to think like a CFO. You really need to stay on top of your numbers. I also think the marketing discipline has evolved over time to a place where being quantitatively rigorous and having as much financial acumen as the finance people has become really important.

We embarked on a marketing ROI project where, over eight or nine months, we broke everything down into two elements: efficiency and effectiveness. On the efficiency side, we consolidated our agency roster and got significantly better at running a really rigorous RFP and negotiating commercial terms with our agencies, be it media buying, creative, research—all the different parts of the agency constellation. That side of the work included getting better at understanding our costs and then being very precise about competitively bidding out the work.

The other side of the marketing ROI project included a number of different effectiveness measures like improved targeting of our digital-media buy, understanding exactly where the money was going and where the best ROI was. We also examined our research activities over time to make sure we weren’t duplicating th

e same study over and over again but were actually building and sharing knowledge.

A crucial aspect of the entire process was the creation of test-and-learn discipline. We did a bit of teaching to make more people aware of the fact that test-and-learn can help you navigate budget constraints by pinpointing the right thing to do. We probably came up with 50 different measures that we’ve been able to put in place and are now tracking.

Reallocating marketing spend: How much is enough?

We put our captured savings in a “pot,” where we measure it and then redeploy it to a series of growth projects. The challenge is to identify which of the many competing growth projects we should put the money into. I think a lot of people in the business thought it would just kind of fall to the bottom line, or the savings would just sit wherever they accrued, or they would be spent on a bigger campaign in that particular market or part of the business. But we designed a pretty clear mechanism around capturing it and redeploying it in a very purposeful way.

That’s because we’d had a peanut butter approach, where everyone was getting a constant percentage of sales. So the marketing budget would literally be the same percentage of sales everywhere, independent of whether the country was growing or shrinking or whether it was a priority or not a priority. So there was a lot of aligning the budget, not on a percentage-of-sales basis, but on a much more sophisticated, what-are-we-actually-getting-on-our-return basis for that marketing spend.

We had what we call “sufficiency” problems in many markets, where the money we were spending was not reaching any kind of critical mass to achieve the impressions needed to move the dial. There was lots of money being spent on paid search, for example, that wasn’t yielding anything like the sort of results that you would expect. So in a lot of markets, we said, “If you’re not going to be sufficient to actually achieve anything, let’s turn it off, and then let’s come back in with something that actually makes more sense for that market.” We also spent a lot of time looking at correlations between countries where we were spending a lot of marketing money and countries where we weren’t, and were actually seeing no difference in the measured business results. That gave us a clue that we might want to pull back on spending in those markets and do some AB testing around whether putting in more or less money actually even mattered.

So there’s been a little bit of doubling down and a little bit of pulling back and not doing things that aren’t moving the needle. There’s also been some more careful husbanding of resources to concentrate on the bigger bets.

Efficient marketing is science, not magic

I’ve spent most of my career in direct marketing, so for me, some of the science has just been rebranding stuff that people in the credit card or the publishing world have been doing for 50 years. But I do think that the cost of data has come down, the cost of the tools has come down, and the level of “real-timeness” of the information has gone way up.

The science is basically just classic: looking at test and control, reading the results, figuring out what worked, what you should do next, what didn’t work, what to stop. There isn’t a huge amount of magic to it. It’s just getting it all in one place and being able to produce analysis and information that people can use to make decisions. What’s changed is we’re trying to make the whole analysis through insight through decision cycle more rapid. Digital marketing has massively enabled that