By now, we all know that big data and predictive modeling are at the heart of any successful and competitive corporate strategy. But making data-driven decisions means more than just selecting software or implementing a BI system; it means making sure the people in your organization understand their roles in applying these systems effectively when it comes to solving problems.
Teamwork is key
A classic problem in analytical system implementation is bridging the disconnect between the people designing the system and the people using it. The business side has the data and understands the problem, but doesn’t know how to prepare data for analysis, much less build the analytics infrastructure necessary to properly model and analyze the data. Conversely, the developers who do have these technical capabilities usually don’t have a grasp of the nature of the problem and what is really needed by the people on the business side. So cross-functional collaboration becomes indispensable.
Develop subject matter experts
It is essential to centralize best practices with respect to how data is used within the organization. This ensures that common methodologies and standards are adhered to when different parties use the tools you have at your disposal. One way to do this is by designating subject matter experts in every department that uses your BI systems. A SME is traditionally a person with a solid understanding of the challenges in their department. Now, that SME must also possess a strong aptitude for data manipulation. They are tasked with creating tailored reports and templates within their department to give the data the desired local context. Additionally, they can troubleshoot issues without having to consult IT. With this structure, management can more easily ensure that data and processes are handled uniformly across the organization. And while every employee should have a basic knowledge of how to use the systems at their disposal, don’t waste time training everyone in functionality that isn’t frequently relevant to their responsibilities.
At the end of the day, local departments are where data-driven decisions will make the most impact on your organization’s bottom line.
Enter the citizen data scientist
We are well aware by now that enduring the rigor to become a data scientist is almost as challenging as finding one to work for you. However, finding people with basic statistics and modeling skills is as easy as looking at the engineers and analysts you already employ. You probably already have a number of what we call “citizen data scientists” among your staff.
The reality today is that some of the tools and technology to do the work of a data scientist are cheaper and more accessible to the common employee. Today’s workers grew up with computers and the internet; they’re frequently more comfortable with technology than previous generations and are more inclined to use free tools such as Codecademy to learn new skills. Obviously, you are still going to need the real data scientists to handle the mathematical heavy lifting. But the more citizen data scientists you create within your organization, the stronger your chances are of unlocking the predictive potency of your data.
Increase chances of success with an executive sponsor
The likelihood of an implementation succeeding and weathering any growing pains increases dramatically with executive support. Of course, the CEO might understand that big data is crucial to success, but that doesn’t mean he or she can remain engaged and visible as the project takes shape. In addition to all the boots on the ground, a senior manager at the executive level who truly believes in the vision should be designated to advocate for the project. This means providing visibility to the BI team’s actions and supporting them with the necessary resources. It is their responsibility over the long-term to remain cognizant of the details and benefits of the project, address challenges head-on and share this awareness and with the other stakeholders involved in the project. A survey conducted by Forbes and EY found that “89% of organizations agree that change management is a barrier to realizing value.” A good executive sponsor will guide a project through this period of change and manage any unexpected circumstances that follow.