Product development. Sales and marketing. Intellectual property. Financial performance optimization. Safety optimization. Go-to-Market. Innovation. These are just a few of the many examples of the disciplines where organizations typically spend time and resources to develop and execute a defined strategy. And despite the breadth of the variables and priorities at play across many of these, there are nevertheless some constants across them.
Before we get into some of these common elements, we first need to quickly affirm what a strategy is – and isn’t. Strategy simply means a set of choices that enables an organization to allocate resources in a manner that achieves a desired outcome in a chosen arena.
Good strategies often include some or all of the following hallmarks:
A good strategy will articulate why you should be focusing on one market or field of play versus another along with how you will be better at serving customers in that market or field of play relative to your competitors.
When done properly, the ‘why’ and ‘how’ of a good strategy essentially amount to a thesis. Theses are by definition speculative and unproven at the outset. The more analytical among us may scoff at the suggestion that unproven ideas, unsupported by verifiable quantitative proof, can comprise ‘good’ strategy. But let’s be clear – uncertainty is inherent to good strategy, a prerequisite in fact. The only strategies that don’t carry at least some meaningful uncertainty are those that seek to simply participate in an existing market and intend to offer a standard product or service. And while that is certainly a strategy, no one would argue that it is a ‘good’ one; particularly if longevity is a priority as the organization is then married to the uncertainty that comes with the potential that competitors will seek to differentiate themselves and reduce the size of the available market for their competitors (i.e. you/your organization).
Organizations that accept fundamentally that uncertainty is a key component of good strategy are more free to pursue differentiation that will provide them the opportunity to lead in their chosen market.
A good strategy is coherent.
It must be logical and make consistent use of data and assumptions. If an aspect of the strategy assumes ‘X’ about a particular aspect of the world, it must accept or apply ‘X’ in all instances where that aspect is contributing to strategic decision making for the base case.
A good strategy must be do-able.
There must be alignment between the requirements of the strategy and the organization’s access to the capabilities necessary to implement it. Actionable components must also be able to be communicated in terms understood by everyone involved its execution.
Your stakeholders must also be able to understand it if they are expected endorse or support it.
A good strategy measures material variables and uses them to adjust throughout execution.
By identifying and measuring the specific assumptions that your organization is reliant upon, you are able to course correct incrementally and substantially increase the likelihood of a successful outcome.
Which application or set of tools used to actually carry out the management matters far less than the simple commitment to reliably monitoring these variables and then iterating accordingly.
Some examples of characteristics common to bad or ineffective strategy:
- Poor resource allocation. Both easy to get wrong and, frequently, easy to fix; both inefficiency and an increased risk of failure are probable consequences of failing to effectively align resources with strategic priorities.
- Economics that do not sustain execution of the strategy long enough to achieve the desired outcome. Certainly more of an entity level existential risk at the shallower end of the capital spectrum but equally dangerous at the project and unit levels for even larger corporations. Be reminded though that uncertainty looms large and a ‘bullet proof’ model isn’t realistic. While you cannot guarantee payback horizons or total ROI, you can optimize the monitoring and deployment of resources incrementally to ensure economic risk is kept to a minimum.
- Shades of insanity. Seeking unique results without a unique proposition or approach i.e. doing the same thing and expecting a different result.
A Quick Note on Uncertainty and Innovation Strategy
Charles Sanders Peirce, widely considered the father of the American Pragmatism movement, once famously said that ‘no new idea in the history of the world has been proven in advance analytically’.
While we covered the reality of uncertainty in strategy at the outset above, it bears restating within the context of innovation campaigns, where failure rates often exceed 90%. If uncertainty exists along the perimeter of organizational strategy development, it comprises the core of just about every innovation investment campaign. While most organizations essentially insist on proof of an outcome before committing resources for mainline strategic initiatives, this isn’t a realistic criteria when developing an innovation investment strategy.
It is important that organizations be honest with themselves with regard to their appetite for uncertainty – and for short-term financial loss. For those that insist on full analytical validation or proof of outcome prior to investing in innovation, very little if anything can ever be expected to come from their programs. Now there may not be anything wrong with that; provided they aren’t also committing resources to R&D or innovation and keep a realistic view of their mobility within their markets. Likewise for organizations who’s innovation strategies include ambitious investments they should proceed with full awareness of the uncertainty surrounding any potential return on investment.