The role of The Chief Data Science Officer (CDSO) is new and evolving – and with evolution comes opportunities and challenges. We’re finding that CDSOs are faced with growing pains on several fronts – and if businesses can’t find a way to properly address some of these issues, the role of the CDSO could be at risk.
CDSOs are joining companies where the business case for their role is left ambiguous. This makes it difficult for them to demonstrate their value the organization. In an effort to define role and responsibilities, CDSOs must work with multiple stakeholders to forge strategic partnerships and carve a pathway to success.
Here’s where to start:
1) Avoid perpetuating “ivory tower” perceptions
The first order of business for CDSOs is to justify their existence and establish how they can contribute value to the organization. Start by building relationships. CDSOs need to work with business owners and subject matter experts to get deep into the business decisions and problems, and identify opportunities where they can use data and analytics to generate insights that enhance decision making. Failure to demonstrate value to the business can raise doubts about the legitimacy of the role.
Often, CDSOs are stepping into companies where there are multiple teams of functional analytics experts managing their data and technology platforms across multiple business units. CDSOs need to work with these existing groups to determine the right organization and operating model that can enhance the value they bring, while not slowing down the existing initiatives of business units.
2) Build Relationships with the C-Suite
Historically, enterprises have focused on traditional data warehousing, reporting and business intelligence in their use of data. But, now that every business function wants to use technology to advance their business goals, the enterprise needs to use data in new ways to make better decisions. Enterprises should use data exploration to inform business analytics. Tapping data to prepare for a possible future is the CDSO’s specialty and everyone’s interest. The CDSO should work with the CIO to educate the C-Suite and beyond on the importance of putting more organizational emphasis on predictive analytics. According to our 5th Annual Digital IQ Survey, C-Suite executives who effectively collaborate are far more likely to outperform their peers.
3) Find the funding
The governance mechanisms for funding in most organizations often confer power to those with the funds – typically P&L owners – and C-level committees. Given the role CDSOs and teams play as a “shared service” traversing IT and business functions, it is important for them to be able to make a direct request for funds as opposed to through one of the many groups they work with or support. To secure funds, CDSOs should pull out all the stops with visualizations, demos and prototypes to “make it real” to business owners how they can enhance their performance with improved analytics.
4) Navigate the vendor landscape
As with any emerging area, the field of data science is filled with a host of start-ups and established companies claiming to offer just the ‘right’ solution for the company. CDSOs must carefully evaluate products based on the organization’s business case – and that’s no easy feat given the multitude of options in today’s crowded marketplace.
Some tools are designed as horizontal offerings that are shallow and not as deep, but more easily integrated across business units. Other solutions plunge into a particular industry or functional area, but are ‘special-purpose’ tools that aren’t versatile nor can be easily integrated with existing solutions.
By the time the company realizes they need something different, executives can sometimes invest a lot of time and money trying to make the product work. It’s a chore trying to move onto something different, especially explaining the shift to senior management. Decisions around when to use proprietary vendor solutions versus open-source alternatives is also a challenge that CDSOs need to grapple with.
5) Change the decision-making mindset of executives
In our recent global Big Decisions Survey, more than 58% of executives made decisions based on their own intuition or experience or those of others. Only 29% relied on data-driven decisions. Executives say they want to use analytics and data, but it’s still not prevalent at companies, in the C-Suite or beyond. Technology companies and younger employees are much more accustomed to using data to steer the ship, but most executives make decisions based on their gut reactions.
Executives can be hesitant to use more advanced data and analytics techniques to inform their actions, especially if the data contradicts what they feel is the right way to go. CDSOs must break deeply ingrained habits using an “art” and “science” approach to data. Creating compelling, visual proof-of-concepts/prototypes with simulation and gaming elements can allow executives to combine their intuition and experience with data & analytics to improve decision making.
We’ve only scratched the surface of the many issues that CDSOs are struggling with as they navigate uncharted waters. We’ll delve into each of these areas more and explore how CDSOs can chart a course for success. In the meantime, let us know if you have any other additions to our list.