Challenges for Data Science Organizations

Its easy for large companies to spend large budget dollars on multi million dollar data initiatives, thereby taking risks that could yield significant rewards. Small to medium size companies dont always have the luxury of a large budget to build their analytics group or solution, and in many cases dont have the time, or patience, to wait for a solution to yield results. Large companies, while having the luxury of a budget, suffer from inertia, sometimes preventing progress.

Overcoming these challenges requires patience, persistence and perseverance. Any Enterprise Information leader must locate the sweet spot by which they can overcome the inertia and doubts in an organization as to the effectiveness of analytics. In order to effectively do this the organization leader, must get buy in from senior level executives, but more importantly target a single group, which if “converted” would become the evangelists for your initiatives.

Companies large and small suffer from a groupthink mentality, which means that although privately they agree, they are unlikely or unwilling to take more of an initiative regarding an unfamiliar technology or process. Some of these groups however, have significant challenges that if an analytics solution can greatly enhance their position, they will not only embrace it but vocalize it. This has the secondary effect of getting other groups “on board”, thus creating a momentum that should be self sustaining in a short period of time.

Any data science initiative, that suffers from these challenges, should forgo, but not completely, proper design, in order to obtain wins that can be used to increase the credibility of the organization and of its efforts. This is synonymous with an invading army that establishes a beach-head in order to secure an area for bringing in more troops and support personnel. The data science leader must think in these terms, because the long term benefit outweighs some of the short term tradeoffs.