Managing Corporate Innovation

Balancing structure and flexibility to build a successful corporate innovation portfolio

1492 Ocean Map by Martin Behaim - Wikimedia Commons
1492 Ocean Map by Martin Behaim – Wikimedia Commons

Working as a corporate innovation consultant, I am constantly confronted with the tension resulting from having to balance structure and flexibility. When innovating, surely, the more flexibility, and the bigger the canvas, the more freedom, the better, right?

Well, yes and no.

The following scene from Robert M. Pirsig’s Zen and the Art of Motorcycle Maintenance between a writing instructor and his student comes to mind. (Emphases are mine).

He’d been innovating extensively. He’d been having trouble with students who had nothing to say. At first he thought it was laziness but later it became apparent that it wasn’t. They just couldn’t think of anything to say.

One of them, a girl with strong-lensed glasses, wanted to write a five-hundred-word essay about the United States. He was used to the sinking feeling that comes from statements like this, and suggested without disparagement that she narrow it down to just Bozeman.

When the paper came due she didn’t have it and was quite upset. She had tried and tried but she just couldn’t think of anything to say.

He had already discussed her with her previous instructors and they’d confirmed his impressions of her. She was very serious, disciplined and hardworking, but extremely dull. Not a spark of creativity in her anywhere. Her eyes, behind the thick-lensed glasses, were the eyes of a drudge. She wasn’t bluffing him, she really couldn’t think of anything to say, and was upset by her inability to do as she was told.

It just stumped him. Now he couldn’t think of anything to say. A silence occurred, and then a peculiar answer: “Narrow it down to the main street of Bozeman.” It was a stroke of insight.

She nodded dutifully and went out. But just before her next class she came back in real distress, tears this time, distress that had obviously been there for a long time. She still couldn’t think of anything to say, and couldn’t understand why, if she couldn’t think of anything about all of Bozeman, she should be able to think of something about just one street.

He was furious. ”You’re not looking!” he said. A memory came back of his own dismissal from the University for having too much to say. For every fact there is an infinity of hypotheses. The more you look the more you see. She really wasn’t looking and yet somehow didn’t understand this.

He told her angrily, ”Narrow it down to the front of one building on the main street of Bozeman. The Opera House. Start with the upper left-hand brick.”

Her eyes, behind the thick-lensed glasses, opened wide. She came in the next class with a puzzled look and handed him a five-thousand-word essay on the front of the Opera House on the main street of Bozeman, Montana. “I sat in the hamburger stand across the street,” she said, “and started writing about the first brick, and the second brick, and then by the third brick it all started to come and I couldn’t stop. They thought I was crazy, and they kept kidding me, but here it all is. I don’t understand it.”

Neither did he, but on long walks through the streets of town he thought about it and concluded she was evidently stopped with the same kind of blockage that had paralyzed him on his first day of teaching. She was blocked because she was trying to repeat, in her writing, things she had already heard, just as on the first day he had tried to repeat things he had already decided to say. She couldn’t think of anything to write about Bozeman because she couldn’t recall anything she had heard worth repeating. She was strangely unaware that she could look and see freshly for herself, as she wrote, without primary regard for what had been said before. The narrowing down to one brick destroyed the blockage because it was so obvious she had to do some original and direct seeing.

The roles structure plays in innovation

Managing scope

Just as in the case of writing creatively, your ability to innovate hinges on whether you can see things with fresh eyes. The problem is, the bigger the scope you are tackling, the more generic your ideas tend to become. This is because you will necessarily have to rely on second-hand information as the area of what you need to cover grows, forcing you to repeat and recycle other people’s ideas.

That isn’t all bad, per se, but it is not necessarily the best way to come up with original insights.

As the instructor in Pirsig’s text points out, to see something with fresh eyes, you need to experience them first-hand. The apprentice-writer finally achieves this by physically going to the building in question, then focusing on the upper left-hand brick.

This is the first role that structure plays in innovation management: To help you narrow down the problem set you are going to tackle. This in turn increases the chances that you will find ways to experience things first-hand, by doing primary research, for example, and thus come up with some original thoughts of your own.

Successful innovation frameworks help you manage scope. This is not to imply that scope is always too ambitious and will always require narrowing down. Granted, sometimes a dollop of added ambition is warranted. But in our experience, more often than not, it is too big, rather than too small, and as a corollary, too unoriginal, that is the problem.

Measuring progress

The second role that structure plays in innovation, is to measure and manage progress.

According to Osterwalder et al. in The Invincible Company, a firm engages in roughly two types of value creating activities: Exploration and exploitation. Both of which are necessary for success.

An established company most likely grew by developing the capabilities needed to exploit and extract value from the original idea that led to its founding. And the aim of measuring exploitation is to ascertain how much you have progressed according to plan.

If the activity, as exploitation is usually about, is one that the company has undertaken many times before, then the relationship between inputs (time and money) and the output (scope) should be well-known and stable. Therefore, metrics should naturally focus on measuring inputs versus outputs, and enable a strategy that focuses on efficiency: Optimizing the input/output ratio.

Input-Output Efficiency - Image by the Author
Input-Output Efficiency – Image by the Author

But when you are in exploration mode, you are by definition in uncharted territory. In that case, progress is harder to track by measuring inputs. The outputs are even more uncertain. And knowing how far along you are according to your original plan is less important than what you actually discover. Christopher Columbus may have been way off his original plan to reach India when he disembarked onto the New World. Yet, there are very few who would define him by his ’failure’ to find a new trade route to India.

Having grown by optimizing for exploitation, most structures, and frameworks that incumbent companies instinctively deploy not only tend to favor exploitation, but can even be counterproductive to explorative activities, which is what innovation is primarily about. Companies risk misallocating resources when they apply frameworks that focus on efficiency, such as how many worker-hours were necessary to reach milestone X, but fail to validate whether milestone X is indeed valuable. Or missing the pivot to unplanned milestone Y, where there was more value to be found.

So, in the context of a specific innovation initiative, we measure progress by how well we achieve customer-problem-solution fit, not (yet) by how efficiently we managed our resources. More on that later.

Managing individual innovations

As explained, exploitation-focused teams should naturally deploy efficiency-based strategies. These are based on a basic assumption that the relationship between project inputs and outputs is known and can be optimized. For example, traditional project management methodologies focusing on balancing cost, time, and cost fall into this category.

Derivatives of this paradigm, such as the RICE framework (Reach, Impact, Confidence, and Effort) are helpful to understand how to best execute already known ideas, given existing constraints. But they are silent on whether an idea indeed solves a problem, is innovative, or even valuable in the first place. In fact, in our experience, given the lack of reliable data that usually characterizes innovation projects at their earliest stages, a premature application of the RICE criteria inevitably leads to prioritizing more of the same old stuff.

This is why so many attempts at introducing innovations by project management, which works great for exploitation, fail.

Innovation teams should deploy exploration-based strategies striving to achieve customer discovery, and problem-solution fit.

Customer-Problem-Solution Fit - Image by the Author
Customer-Problem-Solution Fit – Image by the Author

To structure this process, which can take several iterations of hypothesis-making and hypothesis-testing, let’s break it down into its simplest generalizable structure:

Customer-problem fit

  • Making a hypothesis: Customer X has problem Y.
  • Test: Does the customer have this problem?
  • Result: If yes, then explore solution. If not, then find another problem, another customer, or both, and re-test.

Problem-solution fit

  • Hypothesis: Solution Z solves problem Y.
  • Test: Does the solution solve this problem?
  • Result: If yes, then user-test and design go-to-market. If not, then design another solution.

Solution-customer fit

  • Hypothesis: Customer X will buy solution Z.
  • Test: Does the customer understand the solution Z, and is willing to give something of value for it?
  • Result: If yes, then build. If not, then redesign and re-test.

The above should cover most scenarios, and design thinking-based approaches, with their focus on customer-centric and iterative problem-solving, are particularly well-suited to explorative activities.

For example, in Value Proposition Design, Osterwalder et al. can give you an idea on how you can methodically deploy any of the following tools: Qualitative and quantitative customer surveys, ethnographic studies, rapid prototyping, and user testing, among others, to test the hypothesis framework above, with each deployment taking your innovation closer to a Customer-Problem-Solution fit.

One level up: Measuring efficiency

The third role that structure plays in innovation management is measuring performance. And yes! Finally, something that our good old-fashioned efficiency-based metrics excel at.

If all exploration activities undergo a structured or standardized processes, then, in aggregate, you should be able to determine if a process is more or less efficient than others at creating innovations.

In this regard, managing innovation is a lot like managing an investment portfolio. It is nearly impossible to judge your skill as an investor by looking at the performance of only one of your stock holdings, or one innovation for that matter. However, that assessment can be reasonably made by looking at the performance of your portfolio as a whole, then measuring it against a suitable index, or benchmark.

It is no mystery, then, that once they grow beyond managing just a few innovations, some of the more successful companies adopt the Venture Capital Model to manage their burgeoning innovation portfolios.

But where’s the flexibility?

Innovating is subject to trial and error, which is why it is, to a large degree, a craft. You learn by doing, and the more you do it, the better you get at it. Innovation is iteration.

At first glance, it may seem like processes and frameworks constraint creativity. This is not so. As we have seen, constraints on scope usually force innovators to really look at the customers and their problems, which increases chances of original insights.


However, even within the constraints of a process designed under these principles, there is one major source of flexibility: Its iterative approach.

While the best practice we advocate is to stick to pre-determined constraints within iterations, innovators should also remember that one of the objectives of iterations is to probe for more information on which to base future decisions.

Pivots can, and should happen between iterations, once new information becomes available and merits it.

Structure is required within iterations. And flexibility is provided betweeen iterations. The image that the word pivot itself evokes is appropriate: A pivot, like an articulation, implies that the structure remains rigid while rotating around a fixed point, thus combining both the benefits of consistency (structure) and freedom of movement (flexibility).

In conclusion

An effective framework for corporate innovation management should deliver the following objectives:

  • Develop differentiated value propositions by incentivizing original thinking. This is achieved by scope management, as an exceedingly large scope is the most common obstacle to original thought.
  • Explore and achieve Customer-Problem-Solution fit. This is most effectively measured by a hypothesis testing-based framework, rather than one based by how efficiently we turned inputs into outputs.
  • Efficiency should be measured, not at the individual project level, but at the portfolio level. This allows companies to quantitatively measure and optimize how efficient their innovation process is at funneling ideas into a valuable portfolio of new products and services.
  • Finally, the best practice we advocate is to apply constraints within iterations, which provides structure. In between iterations, you can pivot when you have new information, as the previous iteration becomes the source of information for the next one.

Article originally published in Medium.

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