Analytics technologies are a dime a dozen, and no matter what your organization’s goals are, you can find a tool that helps you meet them. But for all the much-deserved hype surrounding analytics and the benefits it can deliver, there’s often a missing piece to analytics implementations, and it’s frequently the cause of project failures. That crucial missing piece is leadership.
Most problems that befall analytics initiatives are initially thought of as technical or political problems–either the technology isn’t a good fit or powerful enough; or there are organizational issues that prevent the initiative from delivering on the grandiose promises that were made by IT when they sold the project to management. Either of these will kill a project. Both spring from the same well: a lack of leadership.
I believe that leading an analytics project is fundamentally different from leading other IT projects. All the certifications, designations, and belts that you can earn will prepare you for the practical parts of leading an ordinary IT (or any other) project, but analytics projects differ from typical IT projects in several ways, and these differences make leading these projects more difficult.
Bring People Together
Unlike typical IT projects, there’s no natural owner of an analytics initiative. Typically, BI projects start in one department, like finance or marketing. However, analytics–at its core–seeks to answer questions that involve data from across the organization. So, everyone wants to lead the project because it will affect the very core of how they’ll be able to do their jobs. These power struggles are fatal to analytics projects.
Strong leadership can end (or greatly reduce) the infighting. It’s critical to have a single, strong leader who’s politically savvy enough to find and bring together the real power players in each department or business function to create a strong support base for the project. An effective leader will do what’s right for the organization instead of their department.
Bridge the Gap Between People and Technology
Effective leadership is also essential to analytics initiatives because they’re so much more complex technologically than traditional IT projects. As data volumes and types have exploded in the past decade, companies are using new data science methods such as clustering, density estimation, jack-knife regression, neural networks, and other deep data science techniques to spot patterns and perform predictive and prescriptive analysis.
Success with analytics takes a leader who can bring the data scientists and business people together to function as a team. That isn’t easy, because, as technology has become more sophisticated, the gap between the “language” of technical and business people has widened into a gulf. It’s not important for leadership to speak technical language; instead it’s critical that they are able to understand how to communicate business needs to data scientists so that the best tools and techniques can be implemented to solve problems and gain better insights.
Understand the Importance of the Human Element
Speaking of technology, there are many extraordinary analytics tools on the market today. Too often, the analytics team gets blinded by the technology. They begin to think that choosing the right tool and implementing it will be the answer to all their problems. It won’t. The tools, as powerful as they are, lack one thing: the organizational experience and inside knowledge to interpret the data.
Successful leaders understand the potential of coupling powerful technology with the human element. Can the technology take all the data available to it and provide you with insight that you’ve never had before? Absolutely. Can it recommend a course of action based on that insight? Of course. Can it tell you, based on years of inside knowledge of both the organization and industry, whether that course of action is right for your company? Absolutely not. Only humans can do that.
Technology, even artificial intelligence, is limited. Sure, up to a point, technology can automate processes and make some decisions—but it can’t synthesize gut instinct and years of experience to come up with the customized answers for those problems that are maddeningly complex and totally unique to a particular organization. Only the humans who are looking at the answers provided by the technology can do that. Good leaders realize that, and they encourage that crucial interplay between people and technology.
Ask yourself these questions: can the people I want to lead my analytics initiative:
- Bring people together to do what’s right to for the organization?
- Bridge the gap between technology and business to choose the right solution for the issues the company is facing?
- Understand that the technology is limited and needs to be supplemented by the human element?
If the answer to any of these questions is no, it might be time to re-evaluate your team.
Anu Jain, Vice President, Americas, is at the forefront of the analytics, machine learning, and workflow orchestration revolution. Anu is a leader in Teradata’s transformation from a perpetual license model to a service organization that will drive innovation in open source, business solutions adoption, analytics, and workflow. He has deep technology and domain-specific thought-leadership and expertise in ad tech, media, front-office effectiveness, digital media and analytics-powered industry solutions. His expertise in technology-driven business transformation includes big data, cognitive analytics, predictive analytics, data mining, data warehousing, and business intelligence. Before coming to Teradata, Anu worked for IBM and Deloitte Consulting.