5 Proven Strategies to Articulate Your Analytics Team's Value and Performance

A must-read for all data and business leaders.
5 Proven Strategies to Articulate Your Analytics Team's Value and Performance

Chief Data and Analytics Officers (CDAOs) are in the value creation business — use technology as the tool, data as the raw material, and analytics techniques as the process to generate “actionable and impactful insights” to guide decision-making for business “profit and loss” (P&L) owners.

Every CDAO conference or conversation I attended in the past year had a common theme: use cases, return on investment, and business value creation. 

CDAOs must show the CEO or CFO how they add value since they have received the investment in the data and analytics initiatives. However, I have not seen many illustrations on how to estimate the value of the data and analytics initiatives.

Setting up the stage for our discussion


  • Recently, Bill Schmarzo (global big data and data science leader) posted the economics classic “The Wealth of Nations” (1776) by Adam Smith, with two important concepts: “value in use” and “value in exchange”. The things which have the greatest value in use frequently have little or no value in exchange; and, on the contrary, those which have the greatest value in exchange frequently have little or no value in use.

  • In our context, “value in use” may fit in the internal use of data and analytics; “value in exchange” may fit in the external commercialization of data and analytics. 


  • Value can be demonstrated in quantifiable and tangible ways or qualifiable and intangible ways. 

  • Not all quantifiable or measurable numbers are in dollar values. 

  • Value can be portrayed in monetary terms or non-monetary descriptions. 

  • For the benefits valued in monetary terms, we can compare them with the investment an enterprise has made and calculate the return on investment (ROI)

1. Value in monetary terms

1a. Frontline dollar value

This is defined as incremental revenue or expense reduction that can be directly attributed to specific analytics solutions.  

The finance leader in a business unit is familiar with the baseline of revenue and expenses, with all the details on the underlying drivers. 

If a specific analytics solution, such as a predictive response model for a marketing campaign, is added to the status quo, the finance or operational leader can estimate and document the potential uplift.  The uplift can be explained by:

  • Spending the same budget to get incremental revenue, or

  • Achieving the same operational metrics (such as responses or loan amount) by spending less. 

After the analytics solution is implemented and we have adequate time to measure the outcome, we can compare the actual result with the estimated uplift. The incremental revenue or expense reduction is the value of this predictive model.

Most of the time, the analytics solution (such as the predictive model example) can only claim 30-70% of incremental revenue or cost reduction, based on the negotiation of all parties involved.

This claim of incremental value is NOT really double counted in the financial reporting, but only for calculation purposes as a “token” for the CDAO team to keep their score. The team has a portfolio of such analytics solutions. It can aggregate all values in this project portfolio to describe how much impact they have made on the enterprise in a certain period. 

This example shows why the alliance with finance and marketing (or any other frontline operational area) is so important: as the allies of the CDAO team, they can help measure the impact of an analytics solution, and they do not feel any discomfort from sharing the credit with their partners in the CDAO team.

With a well-established practice of “establishing the baseline, estimating uplift, measuring the actual outcome, and tracking the ongoing impact of analytics solutions,” the snowball effect will make the CDAO team a critical partner intricately woven into the operational fabric.

1b. Current budget, expenses, or investments

This value measurement is defined by the most recent CDAO team’s operating budget (all-inclusive: compensation and benefits, training, technology, contractors/consultants, etc.), plus a reasonable markup (such as the overall gross margin for the enterprise or the specific business unit). 

For example, if the data and analytics team has been providing services to the other departments and business units, we can assume the service recipients have received adequate value from sharing the cost of keeping the CDAO team. 

Obviously, this is an indirect value measurement, but it can be a valid placeholder. If more pressure has been building up from the service recipients that they did not get enough value from investing in the CDAO team, the CDAO needs to pay more attention to building the internal alliances to request for more collaboration from the partners or more time for the team to demonstrate value.

This approach helps create a perception of an autonomous and semi-independent business unit: the CDAO team must proactively seek to create and deliver value, otherwise it can be outsourced to any external business entity to perform a similar function.

2. Efficiency gains

The CDAO team can demonstrate various quantifiable benefits, such as time-saving, shifting to more productive (strategic, non-operation-focused) use of human resources, improving morale, helping staff retention by reducing burn-out due to monotonous or manual tasks, and upskilling. 

The time-saving in hours for business frontline staff can be calculated by multiplying the reduced number of hours by the average hourly rate in salary or all-inclusive compensation. 

Workforce morale improvement can be measured by employee engagement survey results.

Staff retention improvement can be reported by the human resources analytics team. 

The benefit of employee upskilling can be measured by human capital analytics consulting firms or estimated by the chief human resource officer.

3. Trendline and benchmark comparisons

3a. Net Promoter Score

The CDAO team can utilize Net Promoter Score (NPS) to measure their performance: first, establish a baseline, then conduct surveys quarterly or semi-annually, and measure trendlines with commentaries from their customers. 

They can also compare their NPS score with the benchmarks in the same service line, industry, or function, so that they can prevent complacency and build a habit of continuous improvement.

3b. Enterprise Analytics Maturity Assessment Score

Several research and consulting organizations, such as the International Institute for Analytics (IIA) or Gartner, provide a consulting service that enables CDAOs to compare their organizations' analytics capabilities with their peers in the same industry or with firms in other industries. The comparison and contrast at certain points of time, plus the trendline of multiple assessments over a few years, can be an input to evaluate the CDAO team's performance.

4. Soft benefit

The CDAO team can help build and sustain an organizational culture that promotes collaboration, continuous learning, mutual appreciation, and community support. This soft benefit is like “brand equity” – compared with an average company or team, people are more willing to join a company or team with analytics leadership and vision. Welcome your editorial revision. With the enhanced organizational cultural brand, more talented professionals are attracted to join the organization, lowering the recruiting cost.

5. New trends

The book “Infonomics: How to monetize, manage, and measure information as an asset for competitive advantage” (2017) by Douglas Laney details the need for a new way to assert economic significance to information. He recommends we need to treat information as important as financial or physical assets and report the value of information on our financial statements.

Another book “Data Juice: 101 Stories of How Organizations Are Squeezing Value from Available Data Assets” (2022), also by Douglas Laney, is a helpful guide for CDAOs and other leaders. 

When analytics solutions are directly linked with revenue for the organization, CDAO's role becomes more visible and influential.


Here is the summary of what I have learned, observed, or practiced in the past 20 years: how CDAOs can articulate the estimated value of data and analytics initiatives. 

  1. Monetary terms: incremental revenue increase, cost reduction, or sustainable operating budget for the CDAO team

  2. Efficiency gains: time saved or shifted, staff retention, morale improvement, and upskilling

  3. Net Promoter Scores and Analytics Maturity Assessments: trends and benchmarks 

  4. Soft benefits: culture, brand equity, competitive advantage 

  5. New Trends in data monetization (internal) or commercialization (external)

Most organizations focus on the “value in use” or the “defensive strategy”; building internal capabilities to utilize data, technology, and analytics to enhance their competitive advantage.  Some organizations focus more on “value in exchange” or the “offensive strategy” because they are in the service or solution business: data and analytics capabilities drive and generate revenue for them.  

I hope to help describe the current practices of estimating value for data analytics teams and invite more experts in the space to share their best practices, so more professionals can benefit from the analytics community sharing.

Note: The article was first published on the author’s LinkedIn blog. It has been republished with consent.

About the Author:

"Mr. Ge” Gary Cao advises CEOs and board of directors on analytics and AI strategy and serves as a fractional Chief Data and Analytics Officer (CDAO) or Chief AI Officer (CAIO). With 20 years of experience as a CDAO and serial founder of internal analytics startups, Cao has had a strong track record at 8 companies with revenue between US$40 million and US$120 billion.

Cao’s journey spans industries including healthcare (provider and payor), distribution, retail and ecommerce, financial services, banking, marketing, and credit/insurance risk. He is an expert advisor at the International Institute for Analytics and Rev1 Ventures startup studio and has been a speaker or panelist on various events and podcasts.

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