Counting down Our Top Ten List of Discovery Driven Planning misses – Part 2 (5 through 1)
Through Valize, Ron Boire and I have been working with clients to use the tools we have developed to bring Discovery Driven Planning / Discovery Driven Growth to life. Although we’ve got years of experience doing this, and over 100,000,000 hits when you search on the term, it’s still pretty jarring to take on a project with a company only to find the same mistakes popping up over and over. As a public service, therefore, we share our current top 10.
#5: Pouring resources into a thing that your parent corporation is not prepared to support
A surprising result from my dissertation research was that there is a low correlation between the market’s reaction to an offering and how enthusiastic its parent corporation is about it. There are products that get met with lots of customer excitement but which the parent company has little interest in growing, and products that companies are wildly supportive of but to which the market’s reaction is basically “meh.”
The recent high drama back-and-forth over the launch of CNN+ is a great illustration (you can read my detailed observations on this situation here and here). Basically, AT&T and Time Warner (parent company of CNN) decided to merge, on the theory that there were synergies to be had (watch out for that word) marrying the customer base of America’s second largest wireless carrier (largest, if you only count smartphones) to a content provider. Time Warner would provide the reason for customers to increase the depth of their relationship with AT&T; meanwhile knowing who those customers are and how they like to spend their time would give the content people invaluable feedback. They spent $84 billion on the tie-up, fended off the Department of Justice and proved toxic to the then-leadership of the group they purchased who left en masse.
Meanwhile, Jeff Zucker, a legendary leader at CNN, strongly believed in the potential of a dedicated streaming service, to be called CNN + and championed the launch, after selling the idea to the AT&T brass, who gave the green light to a $1 billion budget to get the thing launched. About $300 million was spent by the time of the launch. It’s useful to remember that the AT&T leadership is totally used to throwing billion dollar budgets around. Big capital programs is what they are all about.
Fast forward to find Zucker dismissed, the CEO at AT&T who engineered the deal, Randall Stephenson, retiring, and the decision to pursue media assets in the first place basically reversed by new AT&T chief John Stankey. David Zaslav, the new top guy at the once-again-renamed media giant Warner Bros. Discovery had zero interest in pursuing Zucker’s ambitious plans for CNN+. After less than a month, the project was shuttered. And that, as they say, is that.
#4: Justifying a brand-new offering on the basis of some fictional ROI that it will generate – hello, quantification of fantasy.
Have you ever seen a business plan that looks something like this? “The market for X is projected to be $2 billion by 2024, and all we need is to get 5% of that market.” With the revenue number firmly established at the beginning of the plan (because after all, how hard can it be to get 5% of a new market?), the rest of it goes into minute detail about costs so that an attractive net income number falls out at the bottom.
My colleague Ian MacMillan and I were involved in a post-mortem of a venture that had unfolded exactly on this basis by a big bank. The idea was bold – by capturing information about what people purchased, you could cross-market to them. As Mac used to say, “chances are that if I’m buying kitty litter, that unless I have really bad engine trouble, I’m very likely to own a cat!”
This was years ago, before we knew anything about how useful data about people’s purchasing patterns would be to advertisers. But in this case, the idea was not to cross-promote to advertisers, but rather to sell the information to big consumer packaged goods companies. The revenue would come out of their promotion budget, not their advertising budget, because they could divert promotion dollars to targeted selling. The problem? While the team had accounted for the cost of coffee virtually to the last nickel, nobody had modeled out how they were going to extract any revenue from the target customers! They just assumed that if they built the information asset customers would magically come knocking on their door! That one, I’m told, cost over $130 million (at least in expenses the sponsors would own up to).
A related issue was famously named “Capital Market Myopia” by William Sahlman and Howard Stevenson. This is when each participant in an investment scenario makes rational choices for their own participation, but faild to understand the cumulative implications of the decisions everybody else is making. The result? Disaster. Bubbles, overvalued sectors, well intentioned investors losing their shirts and overcapacity. Sounding familiar?
#3: Creating an accelerator, studio, innovation center or whatnot and then shutting it down when it doesn't deliver tangible results in a 24-month timeframe.
Ok, so you want to build a billion-dollar new business because it is going to be the Next Big Thing for your company as competition nibbles away your existing core business. To show that you are serious, you create some sort of innovation place – an accelerator, a studio, a startup lab, an innovation center – some kind of cool-looking space that will house the most creative people you can get your hands on. Then let them set their imaginations free, come to work and do huddles, rethink existing business models and so on - it's exciting! It's big! It's new! It’s Innovation Theater!
It's also unlikely to deliver results on a corporate timeline. My late colleague Ralph Biggadike published one of the earliest solid pieces of research into how long it took an idea to go from idea to commercial launch. His findings? Around seven years is typical. Further, in an iconic article entitled “The Risky Business of Diversification,” he found that it took 10-12 years for the ROI of a from-the-ground-up new business to equal the ROI of a mature one. Another early study by Stevens and Burley found that on average it took working through 3,000 new ideas to create one commercial success.
More recently, Alberto Savoia walks us through the math of strategic innovation, which is a need to have 500 ideas and to kill about 490 of them along the way. It’s an unpredictable process, and you never can tell when the right new thing is emerging.
Unfortunately, the gestation time to come up with a meaningful growth business is often longer than the tenure of the CEO who gave the OK. It is also often longer than the tenure of the team that launched the idea. And it is definitely longer than the investing community wants to hear about. So, have a setback in the core business somewhere and the first thing on the chopping block is the accelerator…incubator…oh, whatever.
To be meaningful, innovation has to be more than one person’s baby. It has to be a capability that is cultivated and nurtured across the organization. For a great read on how such a culture and capability was built, Curt Carlson’s book Innovation is a terrific start. For a more current version, Carr and Bryar’s book Working Backwards is also super useful. To read about two organizations that get it right, this article is a great resource.
#2 The wrong metrics, or no metrics at all! Metrics for innovation need to be based on progress and learning, not lagging indicators like sales.
It seems to me that sometimes the metrics that we create, argue over, adjust and report are little more than some kind of corporate performative art. You can have three kinds of measures in a business.
Lagging indicators are great information, but you can’t change them. They are the result of some action you have taken in the past. Amazon’s Bezos is fond of pointing out how useless these are. As he said during a fireside chat in 2017,
“When somebody… congratulates Amazon on a good quarter… I say thank you. But what I’m thinking to myself is… those quarterly results were actually pretty much fully baked about three years ago… Today, I’m working on a quarter that is going to happen in 2020, not next quarter. Next quarter, for all practical purposes, is done already and it has probably been done for a couple of years. And so if you start to think that way, it changes how you spend your time, how you plan, where you put your energy. And your ability to look around corners gets better. So, many things improve if you can take a long term view. By the way, it's not natural for humans. It's a discipline that you have to build.
Current indicators give you insight into where you are and how things are going right now. Amazon is also very strong at using these, with just-in-time metrics that are embedded in operating processes so that teams can self-adjust.
The hardest metrics to capture are those that represent leading indicators. In other words, information that gives you ideas about what interventions you might need to make now to create your intended outcomes in the future.
You need to look at metrics that reflect an innovation’s progress and promise. You’ll find some good ideas in the book Innovation Accounting by Dan Toma and Esther Gons. The core concept is to look at things like number of assumptions tested, speed through milestones, amount of learning being done for investment committed, and so on. I’ll have a new white paper on this exact topic coming out soon.
TA DA! #1 Treating untested assumptions as facts! Very easy to fall into, very hard to dig out of.
This is the uber indicator that an innovation project isn’t being de-risked in a way that makes sense.
We know that human beings are subject to all kinds of cognitive and decision-making biases. Wikipedia thoughtfully has compiled a huge list of ways in which our decision-making processes can be distorted.
Fortunately, there are a few things that you can do to counteract the all too human tendency to fall into assumptional rabbit holes. Document your assumptions either in writing or digitally. This counteracts the tendency to forget them when new information pushes old information right out of your head. When you have a project review meeting, go back to that list and ask what, if anything, has changed? Add new assumptions as you are making them. Give team members permission to raise questions about why we are making certain assumptions. Be open-minded – just because a question isn’t popular doesn’t mean it might not be important. Amy Edmondson’s work on creating psychological safety is crucial.
As we come together on a decision, a great best practice is something called the “nominal group technique.” That is to have everyone at the meeting, before anything is said, write down their thoughts about the correct response to a question. Then, before powerful people have a chance to speak, get everyone’s best thinking into the conversation. Then begin the debate!
It is also super useful to have project teams report out on their progress to other project teams, should you be so fortunate to have those. As Curt describes the process of active learning, it takes five practices:
Iteration with real time feedback. Think practicing the piano with a master teacher.
Concise mental models. Too many words and people get lost. Keep it simple and they can learn.
A variety of approaches to appeal to different styles of learning.
Small, but cognitively and experientially diverse teams.
Frequent comparisons – like going to the eye doctor, it’s easier to make simple comparisons (“Is option A more clear or option B?”) than to compare complex wholes.
Do you have your own favorites list of messed-up innovation practices? We’d love to get the conversation going.
Meanwhile, at Valize…
Valize was founded to help organizations build innovation and transformation capabilities. It’s a passion project of mine, prompted by my frustration that organizations struggle so much with innovation and growth, even though we know a lot about how to do it right. Further, people who read my books, come to my speeches or take my classes were asking how they could take their practices to the next level.
Hence, Valize. The name is meant to invoke beautiful portfolios and value realized.
If you’d like to work with us, here are some ideas:
Advisory activities in which we train your teams on how to build discovery-driven plans and use those plans to drive learning and de-risk projects. We’ll help the teams define what success should look like, create core documents such as a reverse income statement and deliverables specification and help architect low-cost learning events which we call checkpoints. We also do more general teaching and training on building an innovation proficiency, which often involves workshops and senior team coaching. Our goal is to create self-sufficiency, so we aim to work ourselves out of every engagement we take on.
A software spine that makes it easy to instrument a discovery driven planning approach. We call it the SparcHub (which stands for Strategy, Planning, Asset Review Cadence). It creates a portfolio view of your projects, captures the degree of strategic fit each one has, tracks spending against learning and captures which assumptions you are testing at what checkpoint. You can watch a recorded demo here: https://my.demio.com/ref/ClKpAsUWzDQYdVnJ
Learning modules that go together with typical checkpoints. Currently, we’ve built one on discovery driven planning itself, and five more that cover different aspects of learning about customer needs. We even have a free demo course so that you can sample what we’re building. Sign up for that here.