In our past few blogposts we’ve taken a close look at modern day data strategy. We’ve spoken at length about data truth, data architectures, striking a difference between defense and offense and the value that a Chief Data Officer can bring to a data focused organization. Now it comes time to bring all that we’ve learned together; to look at the key elements that make up the ultimate data strategy.
A C-Suite’s Commitment to Data
It all starts at the top. For any data strategy to succeed there must be real investment from the organization’s decision makers. Anything less than a serious commitment to data will mean that any strategy will be doomed to fail before it starts.
Non-committal leadership will under-resource any data strategy initiatives; the subsequent underperformance will reaffirm their initial apprehension, further minimizing resources directed to the strategy. It’s a vicious cycle that leaves the organization well behind their competitors as the data revolution gains steam. The C-suite, and the CEO in particular, must take the time to understand the incredible potential of investing in data strategy.
On the other hand, when leadership shares their decision-making process with their employees and shows their commitment to viewing data as the company’s most important asset, employee ownership and adoption of your data strategy increases. It’s safe to assume a company wouldn’t invest in something unless leadership didn’t think it will produce their ROI, so leaders should communicate that reasoning to their team and then consistently follow up with employees regarding how often and effectively they're using data to improve their decision-making.
A Clearly Defined Purpose…
Once the organization commits to the data strategy, its purpose must be defined. The strategy’s mission and end goal will rest on the organization’s circumstances, both internal and external. As we discussed in our article on the data strategy spectrum, the purpose will likely lean either towards defense or offense. For example, a business in the heavily regulated healthcare industry which has recently experienced a privacy breach will lean firmly towards defense, while a less-regulated electronics retailer which finds itself attempting to enter a new market will tend towards offense.
A clearly defined purpose allows an organization to better prioritize the work that executing a strategy demands. Purpose leads to direction and metrics, or the the goalposts at which to aim. Your focus on either defense or offense, or perhaps an even balance of the two, will also influence the data sources you use (as discussed in our data truth article) and the architectures that control the data (as discussed in our architecture article).
… That Is Also Flexible and Pragmatic
Perhaps counterintuitively, you also need to have the ability to move these goalposts should your organization’s situation change. The ultimate data strategy is marked by an ability to morph and change as needed – it must be able to seamlessly adapt, if circumstances demand, from a focus on defense one month to a focus on offense the next, or vice versa.
This level of flexibility can only be achieved if you design and build your systems and procedures to be capable of such flexibility from the outset. This task is made far easier if you have a team and leader directly responsible for all things data, which brings us neatly to…
Distinct Data Roles
As we discussed in our blogpost about investing in a Chief Data Officer, the value of investing in the right people to direct your data efforts cannot be underestimated. The magnitude of this investment will obviously be limited by your organization’s size and available resources, but if you find the right people, this will pay dividends well into the future.
A Chief Data Officer is the central figure in all of this, and takes on the responsibility of developing a data strategy, albeit with support from the CEO and other relevant leaders, such as the Chief Information Officer. If data-related work is left to employees for which it is ‘just another thing to do’, your strategy will go nowhere. Data strategy is the sort of big picture work that will inevitably fall down the priority list of anyone for whom it isn’t the sole focus.
Structured Implementation
Once you have the motivation, a plan, and you have constructed a capable team, the final element of the ultimate data strategy relates to implementation. It’s vital that there is a measured, structured roll-out of the strategy. A roll-out which doesn’t overwhelm those involved.
It’s important not to bite off more than you can chew. Set your sights on doing the basics well first. Generating a reliable SSoT (Single Source of Truth) should be one of the first items on the to-do list, as this ensures that your entire data team, and indeed your entire organization, is operating from a common set of trusted facts.
Data is king already, but into the future it promises to become godlike. As of this year (2020), every person generates an average of 2.5 extabytes per day, And that's expected to increase to 463 extabytes per day by 2025. The ultimate data strategy involves commitment, clarity, pragmatism, expertise and a thoughtful approach. If you manage to do all these things well, your organization will be perfectly placed to handle the approaching data tsunami.
