Analytics Enablement – Crucial to CDAOs’ Success

The roles of Chief Data Officer (CDO), Chief Analytics Officer (CAO), and Chief Data & Analytics Officer (CDAO) are getting more popular by the day. NewVantage Partners’ Data and AI Leadership Executive Survey 2022 found that 74% of the firms it surveyed had appointed chief data or analytics officers, or both combined in one role.

The increased focus on data and analytics, and the value it is bringing to organizations is very encouraging for data leaders. On the other hand, there has been increased attention on the short tenure of the CDO/CAO/CDAO. There are multiple reasons attributed to this, but I would like to highlight three from the respondents of the NewVantage Partners’ Survey:

• Just 19.3% report that they have established a data culture.
• Just 26.5% report that they have created a data-driven organization.
• Just 39.7% report that they are managing data as a business asset.

Though these are broad causes based on various factors, I strongly believe a focused Analytics Enablement Program can help organizational data leaders make progress by achieving an outcome-driven analytics value chain.

Analytics Enablement Program

The goal of the Analytics Enablement Program within organizations must be to provide access to analytics to “everyone” within an organization. In other words, allow all people within an organization access to insights that lead to actions eventually driving expected outcomes.  

Now, I might have raised a few eyebrows with my statement above about providing analytics to “everyone.” I justify this as a strong proponent of a data-driven/insights-driven culture.

The Analytics Enablement Program will:

• Enforce the importance of a data governance framework

• Force data quality management as a key priority

• Lead to establishing enterprise-wide data and analytics literacy programs

• Enable an insights-driven culture

• Establish a feedback mechanism to continuously learn and improve

Analytics enablement programs from my experience have been a combination of multiple sub-programs. Below is a representation of an ideal analytics enablement program at a high and somewhat generalized level. It is a combination of the data governance program, data quality management program, data literacy program, and what I am vouching for, that is yet to catch fire, the analytics literacy program.

DATA GOVERNANCE

Data governance is the most popular and often beaten-up program within the entire data management ecosystem. It is always complicated to execute large enterprise-wide data governance programs, but every organization knows the challenges they face with the lack of an effective data governance program.

Organizations these days mostly understand the “it all comes down to the data” or “garbage-in, garbage-out” analogies, but just to reiterate, for an effective analytics enablement program, the data must be in top shape. In other words, various factors around data decide the success of an organization in being analytics driven or insights driven.

DATA QUALITY

Having the right data governance framework in place and the right ownership that is willing to take on the responsibilities of defining the varying range of quality will enable data quality management within an organization. Under the newer and larger “data enablement” umbrella, this becomes a critical element for data democratization.

DATA LITERACY

The ability to understand the language of data is often assumed and misinterpreted. Data literacy programs are created to address the earlier defined “perception problem” and enable organizational talent to be more effective in their day-to-day decision making.

Data literacy programs, at various levels of maturity, can be extremely effective in the success of analytics enablement programs.

DATA DEMOCRATIZATION

Addressing the four critical foundational steps in data management above provides confidence to the data leader for democratizing organizational data. Data democratization can be considered the first step in successfully enabling data-driven culture.

• Data Discovery

A key element for internal analytics stakeholders is their ability to easily find and access the data of their preference fast. I have noticed many highly invested analytics users becoming disengaged when they are not able to find the data they require to perform their day-to-day job. As a result, data discovery becomes a key foundational element for a successful analytics enablement program.

• Data Catalogs

Another major challenge that limits an insights-driven culture within the organization is the lack of an enterprise-wide inventory of all data assets. Data catalogs can help provide visibility for that analytics community hungry for data and looking for opportunities to identify deeper insights. This can be a significant driver for analytics enablement.

• Data Ownership

A major reason for analytics initiatives not driving the expected results can be tied to what I call the “perception problem,” Not having an owner-defined data element allows stakeholders to perceive an insight in the way they understand. Identifying data owners is a critical part of a data team’s role, but finding an invested data owner that is willing to support and take on the responsibility of the data element is much more of a practical problem.

• Business Glossary

Another classic case that has been a headwind for the success of CDOs and the overall data culture within an organization is the data glossary. Stakeholders having access to data and insights without having proper definitions is like having access to a powerful new machine without proper instructions. I have been in organizations where the term “customer” gets defined in multiple ways. For example, the marketing vs. finance definition of customer varies significantly.

ANALYTICS LITERACY

Most organizations overlook analytics literacy or ignore the need to explicitly call this out. The reason to highlight the importance of analytics literacy is tied to the importance of communicating the insights identified by data subject matter experts or super users. Being able to use easy-to-understand visualizations and communicating the story is the major goal of the analytics literacy program within an organization. I have been in organizations that have spent a significant amount of money training the super user communities on data visualization tools. I would consider only a quarter of them successful. The goal of analytics literacy must be more focused on the art of storytelling and less on colorful charts.

Though I call this last, analytics literacy is a major measure of the success of the analytics enablement program. It can also be a major contributor to executive buy-in and future investment.

I would like to close by emphasizing the obvious. Ensuring a renewed focus on the existing data governance, data quality, and data literacy programs will support democratizing data. Adding a structured analytics literacy program to it will ensure the analytics community is empowered with everything they need. Together, these programs will result in overall analytics enablement across the organization.

About the Author

Phanii Pydimarri is the Senior Director of AI and Advanced Analytics Products at Stanley Black & Decker. His primary responsibilities include driving commercial value using embedded AI and advanced analytics on world-renowned Stanley Black & Decker products. Pydimarri is a global leader with experience across digital transformation and end-to-end data management. He has showcased successes by driving growth and operational effectiveness at Fortune 500 organizations.

Pydimarri started his career as a consultant, working for clients across industries and functions. He is outcome driven and passionate about solving critical business challenges using digital and data solutions. He has extensive experience establishing data enablement across various public and private sector organizations.

Pydimarri has showcased data as a value-added resource for driving growth and customer success at many global organizations. He recently completed his Executive MBA at Kellogg School of Management. 

Pydimarri is a member of the CDO Magazine Global Editorial Board.