This guest post is by Sandeep Sacheti, VP of Customer Insights and Operational Excellence at Wolters Kluwer Corporate Legal Services, our parent company. This is the first in a series of posts that Sandeep is contributing to the Wired Innovation Insights blog. Sandeep’s message is particularly salient in the enterprise legal management space, where change often requires buy-in from multiple business functions.

 

Most popular big data stories seem to revolve around individuals who have found an interesting mash up between seemingly unrelated topics and discovered a previously not thought of correlation. These stories are solutions looking for problems rather than identifying a problem and providing a call to action. “Gee whiz” graphics can certainly attract readership from a data analytics novice but in the real world where real companies have revenues on the line, data science is fundamentally not an individual sport but a highly collaborative exercise.

Because processes are stuck in people’s heads and change is resisted, the data that is siloed in businesses must first be drawn out. In order for companies to benefit from big data, data scientists and inquisitive minds alike must bring key stakeholders along for the journey and embed a new way of doing business for the future.

Often, data science is perceived as clever model building or machine language algorithms.  Today’s data science should take a company along four phases of a journey; data management, data analytics, voice of the customer and core process redesign. The successful data science program requires people – data scientists and inquisitive individuals alike – to understand business challenges, listen to customer feedback and engage with front line staff (from customer service, product, operations and IT). It leads to a collective call to action based on data-driven hypotheses that have been back tested, can stand the real-world test and control conditions, and options that leadership and staff can rally behind.  Finally, the new way of doing business gets embedded in the core processes of the company and outlives the one-off analysis.

The complexities and abilities of a data scientist or data science program are still not fully understood. Broad engagement is the only way meaningful change takes place. Data-based insights need to be communicated in the language of the audience, sometimes in a graphical form and always in a way that wins the hearts of those creating a collective desire to change. In order for a company to see the benefits of a data analytics program, data scientists must paint a picture of the potential new reality that can be achieved, showing the organization a path to get there and setting conditions for creating the momentum to change.

None of this is new, but for the world to benefit from the massive potential of data science, more than science must be done.  Data scientists have to engage. And thus, analytics is not an individual sport, it is fundamentally a team sport and it is more rewarding that way.