Introduction
Tellius recently joined 300+ data and analytics executives in Boston for the 8th annual Chief Data & Analytics Officers (CDAO) Conference. During this 3-day event, top data and analytics executives from the world’s leading firms including Colgate Palmolive, JPMorgan, Nationwide, Verizon, Fedex, Novartis, and many more came together to share best practices for scaling business value from data and analytics.
During the keynote session, CEO & Founder of NewVantage Partners pointed out that in a recent executive survey, 91% of respondents have increased investment in data last year but only 26.5% claimed to have successfully created a data-driven organization. Put another way, 73.5% of respondents struggle to create a data-driven organization. Roadblocks include:
- Difficulty quantifying/articulating tangible business value from data and analytics initiatives
- Being seen as a “tax” on the business; a back office function; or simply as an “order taker”
- Inconsistent expectations of the CDAO role and lack of boundaries/ownership
- Proliferation of tech stacks/tools and subsequent training cost
- Data literacy; ethics challenges; change management; complacency and groupthink
- Difficulty scaling analytics adoption and efficiency to operationalize analytics into the business
Luckily, CDAOs shared best practices to tackle these challenges. Here are the 10 takeaways:
10 Tips For Becoming a Data-Driven Organization (from 300 CDAOs)
1) Start with the business question
Colgate Palmolive’s Chief Analytics & Insights Officer raised an important point that analytics teams should start from the business question and its link to the bottom line/ strategic firm direction so as to position analytics as powering business growth, not building shiny tools that nobody understands. By beginning with initiatives that the business agrees on and supports, analytics teams avoid the trap of creating wonderful models and dashboards that few actually leverage to their fullest.
2) Articulate the Value
Articulating the value of data and analytics initiatives was a hot topic at the conference. At one roundtable, the CDO of Morningstar shared a humorous glimpse at how NOT to articulate value and gain buy-in for initiatives:
Instead, describe the value-add to clients, not the brilliance of engineering. Additionally, since people never forget about losing money, frame data and analytics investments in terms of minimizing risk, followed by showing the change in cost savings, growth, and cost avoidance. One CDAO pointed out that it can be hard to quantify the value of Master Data Management (MDM), for example, but it is possible to perform a before/after analysis and show the dfferential’s impact to earnings and top line sales. Other CDAOs reminded the conference about keeping value articulation straight forward and measurable. For example, an initiative supporting revenue creation or reduced time to market might be measurable by clicks.
3) Share the Story
Value articulation is never an exact science, and analytics “wins” can be absorbed by the business. But the key insight shared was that analytics leaders need to have the business present the value they’ve derived from analytics and that the analytics solution is only delivering value if business partners feel and see the value otherwise the analytics initiative is purely academic. And to do that, it’s important to tell the story and internally market data and analytics successes. The CDAO at Sun Life Canada added that many issues on the path to becoming a data-driven organization relate to people and to never underestimate the power of change management, communication, and compelling stories.
4) Balancing Offense vs Defense
Another topic raised at the event was finding the right balance between analytic Offense and Defense activities. Offense includes bringing in new clients, growing revenue, monetization, and innovation. Defense includes retaining clients and risk mitigation through governance and compliance. From the sessions and in casual conversations with CDAOs, it emerged that the ratio of Offense to Defense varied by industry, maturity, and is always evolving. Heavily regulated industries like Financial Services tend to focus more on Defense (75-80%) whereas CPG firms can pursue Offense 100% via innovation and driving new channels of growth. Regarding maturity, the CDO of American Express shared that her firm was transitioning from 90% Defense to more Offense thanks to successful governance initiatives. The CDO of BNY Mellon reminded fellow Financial Services colleagues that if you don’t do offense, you’ll always be doing defense!
5) Democratize & Scale through Self-Service
To overcome scalability issues and drive analytics adoption while overcoming data bottlenecks, democratization and self-service initiatives were a hot topic. Many CDAOs agreed that scaling self-service was a key part of making the firm more data-driven and increasing analytics maturity. An executive from Verizon shared an story how, during the early days in a previous form, when he asked the analytics team if they had data-driven answers to key business questions they answered “yes” or “I can get you that answer” to question after question but when he asked them if anyone else in the organization could similarly answer yes there was hesitation — driving home the importance that all levels of the business must be empowered with data. At the same time, scale and efficiency was highlighted as hugely important. One executive reckoned that the amount of money spent on local solutions is actually more costly than had a solution been planned and built for scale in the first place.
6) Go fast, 80/20 rule
Multiple leaders pointed out that the old adage to not let perfection get in the way of good enough, and speed wins, both apply to analytics. Getting the right answer in minutes versus weeks is an unfair advantage. One CDAO humorously said “In a bear market, you can’t outrun the bear but you can outrun the guy next to you!”. Other CDAOs pointed out that if you try to get your data 100% modernized, or 100% governed, you’ll always be chasing that and won’t actually be getting value from that investment. The 80/20 rule applies: 20% of the data/effort solves 80% of the problems. The last 80% of data and effort only solves 20% of the problems that may end up being more niche. So organizations should get started using their data rather than waiting to reach perfection with it.
7) Collaborate and Product Mentality
A related topic emerged regarding improving collaboration and breaking down silos between data, analytics, and business teams. Rather than a “throw it over the wall” mentality – where business users throw work over to analysts who throw it over to developers and IT – the conference emphasized the importance of having a “product” mentality whereby analytics is treated like a product serving internal and external customers through strong collaboration and ownership.
8) Promote Data Literacy
Throughout the event, multiple CDAOs reiterated the criticality of improving data literacy throughout organizations. To these ends, they recommended demystifying jargon that creates fear; simplifying concepts; hosting training sessions; upskilling the firm on new tools; providing analytics academies that educate leaders and front lines on fundamentals; introducing data stewards/ custodians to be ambassadors of the data-driven culture; monthly forums consisting of data and non-data people; and utilizing tools that upskill/uplevel with high degrees of built-in explainability.
9) Ethics & Data Responsibility
CDAOs agreed that ethics and data responsibility was critical. Algorithms impacting humans should go through an ethics control team to answer the question “I know I can do this, but SHOULD I do it”? CDAOs also pointed out systemic bias built into data as a challenge, and that finding a better way to automate bias detection is a growing need. Looking ahead, CDAOs projected that ethics will likely increasingly fall under their purview to ensure organizations responsibly use data.
10) Keep it Human
Several CDAOs cautioned not to underestimate the power of empathy, emotional intelligence, and solid change management coupled with communication efforts for aligning with the business. Business partners who have run things for 30 years don’t change their minds with fancy math. Influence instead by deep empathy. As one CDAO summarized, “building models is easier than driving real change”.
Conclusion
Summarizing three jam packed days, 55 sessions, 80 speakers, and lots of advice from leading analytics executives was no easy task. MANY more insights were shared that were not captured here. What impressed us the most was the passion and energy of the analytics leadership community, the joy of new connections made, and the depth of thought and insights shared. Here are just a few more parting word of wisdom from the nation’s top analytics leaders:
- Regardless of background, make sure to learn domain knowledge and how your organization makes decisions.
- Show deep empathy by putting yourself in the shoes of the business decision maker.
- Success is based on credibility with clients and business decision makers. Invest the necessary time to build strong business relationships.
- Be humble. You’re not the smartest person in the room.
- Never feel like a victim. Be the change agent.
About Tellius
Tellius is an AI-powered Decision Intelligence platform that helps business and analytics teams scale their analytics impact through self-service augmented analytics, expediting time to insights and smarter decisions. Download the eBook to learn more about Decision Intelligence and where it fits into the modern analytics ecosystem.
