Where will your Big Data resources go after your strategy successfully completes?
Have you ever purchased a creme brulee torch only to wonder what to do with it after you've made your creme brulee? I love to cook and my drawers and cabinets are cluttered with specialty tools, spices, and instruments that are rarely used if ever.
Executives who embark on a Big Data strategy face a similar issue. Succeeding with your strategy requires an investment in specialty resources: data scientists, information management experts, and specialized technology. And even though your strategy has a relatively long-term horizon--there's an end in mind. What doesn't terminate after your strategy is complete are the operational expenses for all the technology and special talent that you've enlisted to obtain your vision. The time to realize this is not at your victory celebration. That's why, you must determine in advance where your Big Data resources will go after your strategy successfully completes.
It's not that hard to say goodbye
For some reason, most executives feel they have the responsibility to keep highly paid data scientists on the payroll, but that's not true at all. Data scientists are in a class of professionals that is supported by an industry that extends far beyond the walls of your organization. The same applies for leaders and managers that specialize in getting results from data scientists and other analyst species. Furthermore, this industry is in scorching hot demand right now, and that's projected to continue for the foreseeable future. So, although your specialized resources will be loyal to your company if you give them the right reasons, they have options outside of your company. You shouldn't feel obligated to keep them if you no longer anticipate a valuable, residual contribution to your organization after your strategy completes.
If this is your tact, you have a responsibility to plan for their exit. Let's say you've identified three possible products that may fit your target market; however, you need a Big Data strategy to determine how these products should be positioned. Since you don't have the capability in house, you'll need to hire a few data scientists, an additional marketing expert, and a few leaders who specialize in managing highly talented information specialists. This team will easily cost a few million dollars each year, but it makes sense for your strategy because you have an upside of over $50 million.
Before you launch your Big Data strategy, you determine that the value of having your specialized team will not survive the actual strategy. Once the products are vetted in the marketplace and the innovations are complete, it all becomes an operational issue that doesn't require capabilities over and above what you currently have. If this is your direction, the moment you assemble your new Big Data team, you must have an exit plan in place to communicate with them.
Your plan should include helping them find another job after your strategy completes. It's the same process followed in a responsible downsizing; however, you have a much better timeline to work with. Even a short strategy will run at least two years; this is a lot more time than most people get when they transition out of a company. Also, you must be honest with your resources upfront if this is your direction--it's your ethical responsibility. By partnering with your resources in this way, you'll ensure they not only do an outstanding job for your strategy, but also prepare for their eventual transition by carefully documenting results and experience.
Let's stay together
If however you decide to keep your resources after your strategy completes, you must plan for that as well. There are three key reasons why you would want to retain your specialized task force: sustainable innovation, support for other core competencies, and permanent cultural realignment centered on analytics. Of the three, sustainable innovation is the most compelling reason I would consider.
Innovation is the lifeblood of an organization. Legendary management consultant Peter Drucker identifies innovation as one of only two basic functions of any company (marketing being the other). Regardless of your strategic driving force (e.g., products offered or market driven) innovating with information is a powerful way to build a competitive advantage and these resources will be extremely useful in that pursuit. The challenge is to make their function operational instead of strategic, but it is worthwhile challenge to overcome. Building an innovation process that will continually produce information solutions is not a bad place for most companies.
Of course, that's not the only reason to keep these highly-skilled resources around--number-crunching comes in handy for a lot of core competences. The easiest function to build an economic case for is marketing. If marketing is one of your core competences, there's a likely chance that Big Data analysis will fortify it. For example, sentiment analysis--an analytic technique commonly associated with Big Data--is a progressive way of staying in touch with how your market feels about your company and its products. Marketing is not the only area where Big Data analytics can help--Finance and Risk Management are also natural fits for your Big Data team.
Finally, if your enamored by the idea of transforming your company into a data-driven juggernaut, don't be so quick to release your Big Data strike team. Many organizations are revisiting the old quality mantras of the 80's because information is in vogue like it's never been before. Aside from its fashion appeal, there are very tangible reasons why an organization would undergo such a seismic shift in culture. Information prowess is the new normal; companies who don't embrace this idea may find themselves prey to the ones who do.
To retain or not to retain--That's not the question
When it comes to Big Data resources, it's wise to heed the advice of Dr. Steven Covey and "begin with the end in mind." You can choose to keep your resources to further enhance your business or release them to accomplish bigger and better things--there's no right or wrong. What is important is that you decide what to do with them before you begin your strategy and clearly communicate to them what your long-term intentions are. If you're currently contemplating a Big Data strategy--or even midstream in one--take some time today to decide your exit strategy. This will not only keep you intact ethically, but it will ultimately maximize the use of your resources.