Recently, the InnoStreams team was discussing an article we came across, about the culture at Amazon, and their willingness to experiment and tolerate failure. Isn’t this what the consultants have been telling us for so many years? Of course, few companies have found it easy to execute in practice. But Amazon was able to pull it off.
Perhaps software can help companies adapt to change by building a culture of rapid experimentation to develop clarity around new opportunities. In this blog post, I’ll try to peel this onion – how do you get to a culture of experimentation?
So you’re an engineer, and wondering why this is anything new. After all, faced with uncertainty, a good engineer/scientist tries to frame a hypothesis, establish an experiment, and then go about validating or invalidating the hypothesis to generate some key learning that moves you toward a larger objective.
Or maybe you’re a newly minted marketing analyst. You know how to do landing-page conversion tests, A/B testing, etc. and assume these are commonplace. There now exists several analytics tools to support this kind of experimentation.
Perhaps you’re not stuck in a departmental silo, and are an expert at Agile Tango. The Agile approach common in the software world often pairs product managers and developers. So naturally you’re all working together in a smooth dance, and yet…
- Agile project management usually works within the context of an existing validated business opportunity, and not to define entirely new ones. The focus is on user experience definition and prioritization, tasks and responsibilities, schedule, etc. — not in the core innovation task of resolving fundamental business uncertainties around an opportunity.
- Agile is still largely a software company methodology, although several physical product companies are experimenting with Agile as their world becomes more digital.
Where is the Corporate Finance view in all this? This is where any sort of tango gets real awkward.
Organizational agility to define and validate business opportunities is driven fundamentally by a willingness and capability to experiment at a BUSINESS level. A Business Experiment is a coordination of activities from three perspectives – to determine what you are building, why you are building it, and how you are building it. To support this coordination, Finance must be on the same innovation-page as R&D and Product Management.
In practice, this means that a solution team might develop an initial idea through an evolving MVP (say following Agile). A product team might develop the business model iteratively (for example, using Lean Startup as a methodology on top a Business Model Canvas). Similarly you need to develop the value expectations from an idea. The financial team needs to keep pace. In the early stages of evaluating a new opportunity, you may have insufficient knowledge to do any sort of detailed cost or revenue model. But typical large enterprise financial processes ignore this inconvenient fact. They still go through detailed modeling, using some sort of sensitivity/range estimation around key parameters and associating confidence levels around those estimates. Presumably the ranges and general confidence tightens as we go through the process.
This still sets up Finance as a gate-keeper to innovation, as opposed to fulfilling the equal partner role in innovation. Financial commitments are admittedly a risky business, but not taking appropriate risks is perhaps even riskier. So how do we address this?
We believe that the financial perspective must be an integral consideration of the innovation effort. Initial modeling of value, especially as the problem space is defined and the first look at a solution is taking shape, needs to be very lightweight. As problem/solution validation phases complete, the financial team must work closely with the product and solution teams around revenue and cost structure to begin a preliminary view of the inflows and outflows expected from the novel opportunity. And more importantly, risks need to be identified and explicitly clarified, as an integral part of assessing the “real expected value of the opportunity.”
As the project develops and sharpens in resolution around how to scale the demand — and consequently, scale the solution — the financial model will continue to evolve. When the innovation projects reach Prime Time, and the focus is on optimizing the revenues and margins, the financial modeling becomes even richer.
Clearly, all this only works when the teams are able to coordinate their activities smoothly. It may seem complicated, but with the right tools in the right hands of your organization, you can drive organizational growth around an experimentation and learning mindset. Contact us to see how we can help you.
Originally posted at InnoStreams
