Updated: Feb 10
Having done a few of these, I have come to appreciate what contributes to the right Data Strategy. These are the characteristics I feel a successful one must have. It pays to remember these as a check.
Executive-sponsored Executives today see data as strategic assets. Unfortunately, many organizations have a hard time harnessing the value in data because of many varied factors. One thing is for sure, a Data Strategy sponsored at the highest level will benefit from the proper attention, will have the A-team assigned to it, and will be followed-through because executives will expect tangible results.
Unifying Another characteristic is that the Data Strategy is not a single-department deliverable, but an enterprise-level one, much like a Digital Strategy; everyone that matters has been consulted and is on-board; they own it! There is unity, a consensus around it. It is a real collaborative effort. Most times, executive pressure certainly lubricates teamwork to get there. Everything indeed is related.
Adequately resourced (in time and people) We cannot do a great job of a Data Strategy in a week. Enough time must be allocated to discuss the issues, socialize them and agree on them. Rushing things in this respect is like rushing a business strategy: quality is much more important than meeting a deadline. Allow enough time to include everyone that needs to be involved and to have an integrated product. The same goes for the quality of the team: Go broad and choose your best. It will be worth it.
Done to its full extent There are many moving parts in a Data Strategy (see our Framework), but they are all equally important, if not critical. Like links in a chain, it will be as healthy and as useful as the quality and effort put in the definition of its components.
Awareness that it is a culture to be data-driven Organizations are not equal in this respect. Some will have a harder time getting there. Change management and leadership will be so important to execute the Strategy that we often talk of two "governances": the Data Governance, and the Analytics Governance. There will be selling involved, forums, maybe a buddy system, and leadership required. Do not underestimate the people aspect - it is probably the most important.
Bonus characteristic: it strikes a balance between defense and offense A strategy is meant to give us focus, filter out the noise, and be clear about where we are going and why. Think of offense being about maximizing opportunity with data, making it as easy to access as possible, creating new products based on its insight, automating analytics as much as possible, etc. Think of defense as essentially being careful to protect the data, explain how we transformed it, optimize storage and standards, etc. Depending on your industry, a great Data Strategy will be explicit as to where it stands on the spectrum.
Defense tends to aim for a single version of truth whereas offense accepts that there will be multiple versions of the truth. This last one may sound blasphemous, but if speed-to-market and flexibility are essential, we have to compromises - the risks need to be managed, that's all. Good news: there are ways to do that today!
Conclusion If anything, a Data Strategy is about business outcomes. Technology is essential, but if the conversation does not naturally and regularly circle back to the business goals and objectives, something is off. Get assistance from outside to keep you on track and to make sure you cover the full scope of the work.