Business relationship managers today have new techniques to make data science stickier. Mix it up for greater data-enablement adoption.
The organization knows that data is the future. Data is required for making the best decisions. Data-driven organizations are more profitable. As a result, they can give back more socially by leveraging data to develop better insights. Then why is it that in our last meeting, data wasn’t used to make decisions? Because change is tough.
Great CIOs serve as evangelists for technology and innovation by identifying new, untapped opportunities to enable business objectives and leapfrog the competition. We can’t, however, do that alone.
The role of the business relationship manager (BRM) has exploded over the last twenty years. The BRM has always been critical for successful convergence between IT visionaries and business partners, but it was only recently, in 2013, when Aaron Barnes and Vaughan Merlyn started the Business Relationship Institute (BRM Institute), that the concept of the BRM as a champion of our business partners started to take off.
Tilting the classic lens for change
What if we’re leading change all wrong? The book “Make it Stick: The Science of Successful Learning,” by Peter C. Brown, Henry L. Roediger III and Mark A. McDaniel highlights stories and techniques based on a decade of collaboration among eleven cognitive psychologists. The authors claim that we’re doing it all wrong. For example, we attempt to solve the problem before learning the techniques to do so successfully. Using the right techniques is one of the concepts that the authors suggest makes learning stickier.
Rolling out data-management initiatives is complex and usually involves a cross-functional maze of communications, processes, technologies, and players. Our usual approach is to push information onto our business partners. Why? Well, of course, we know best. What if we changed that approach? This would be uncomfortable, but we are talking about getting other people to change, so maybe we should start with ourselves.
Business relationship managers stimulate, surface, and shape demand. They’re evangelists for IT and building organizational convergence to deliver greater value. There’s one primary method to accomplish this: collaboration.
The BRM should start with a series of data workshops with specific data-management problems to solve. Frame the data-management problems for the leadership teams into four categories:
- Data requirements
- Data-use cases
- Data modeling
- Data implementation
These categories will offer a good bench from which to develop questions that business partners can validate from a scientific perspective. They’re building knowledge so they can ideate around existing problems to discover new opportunities.
Interleaving concepts to create texture and knowledge depth
The BRM is tasked with increasing awareness of data-management practices such as acquisition, cleansing, and modeling or with data principles like data independence, integrity, and consistency. In either case, the information is often presented in chunks or concepts that build. As it turns out, this isn’t a great way to communicate a new concept.
Interleaving is a learning concept that describes the process of students mixing, or interleaving, multiple topics while they study to improve their learning. However, blocked practice is what’s classically taught—study one concept, master that, and then—and only then—move on to the next. It’s been proven that learning retention using the interleaving method lasts months, not days. Studying related skills in parallel improves retention.
The classical building approach is AAABBBCCC. First, we teach about AAA. Second, we teach about BBB. Third we teach about CCC. The problem is that, by the time we get to BBB, the concept is so boring we’ve already lost people. Interestingly enough, it’s not that the data-management concepts are too complex but rather the opposite—they’re straightforward and make sense.
Interleaving involves using the ABCABCABC approach. First, we cover each of the three ABC concepts. Second, we cover the ABC concepts again using different examples. Third, we cover the same concepts again, only this time use other data and examples.
Applying this methodology to data science , the BRM exposes business partners to multiple versions of a problem, which changes the problem and complexity. Wait, wouldn’t that confuse folks? Yes, you’d think it would. However, as it turns out, we’re holding their interest for longer and, as a result, they internalize the concepts better. We’re no longer pushing concepts. Our business partners are pulling them from us.
Fluency isn’t the same as understanding
Speaking of data science, transformational change isn’t the same as executing on it. Be mindful of those players in your organization that have a lot to say about data science. They might be fluent in the language of data, yet, somehow, they still don’t get it. They have no history of executing and delivering data initiatives.
To be creative, we need a better understanding of the problem space in which we’re trying to find a solution. Being creative and being knowledgeable are both necessary. It’s difficult to be creative and present solutions to problems without the knowledge or a foundational understanding of the concepts.
Lean on the business relationship managers within your organization to champion change. Challenge them to teach the concepts of data science differently. By shifting from pushing information onto your business partners to having information pulled, you’ll change the conversation from, “Here’s some data you’ll find useful,” to “Where can I learn more about this data concept?”
CIOs are the evangelists for innovation. BRMs are the champions of change. To make your data science initiative sticky, you need both roles to think differently to enable continuous value delivery. How about starting from the concept that learning about data science can be fun? It’s not as crazy as it sounds. All you need is a little creativity.