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Because ROI is a financial concept, it can be difficult to apply ROI to anything that produces intangible value.
It is a lot harder to apply ROI to functions like data and analytics than it is to apply it to functions like sales without misrepresenting its true purpose.

Our Advice

Critical Insight

The standard ROI formula cannot be easily applied to data and analytics and other critical functions across the organization.
Data and analytics ROI strategy is based on the business problem being solved.
The ROI score itself doesn’t have to be perfect. Key decision makers need to agree on the parameters and measures of success.

Impact and Result

Agreed-upon ROI parameters
Defined measures of success
Optimized ROI program effectiveness by establishing an appropriate cadence between key stakeholders

Position and Agree on ROI to Maximize the Impact of Data and Analytics Research & Tools

1. Data and Analytics ROI Strategy Deck – A guide for positioning ROI to maximize the value of data and analytics.

This research is meant to ensure that data and analytics executives are aligned with the key business decision makers. Focus on the value you are trying to achieve rather than perfecting the ROI score.

This research includes a guide on how to approach ROI when it comes to data and analytics. It also contains a ROI strategy mapping tool to complement the activity mentioned in the research.

2. Data and Analytics Service to Business ROI Map – An aligned ROI approach between key decision makers and data and analytics.

A tool to be used by business and data and analytics decision makers to facilitate discussions about how to approach ROI for data and analytics.

Position and Agree on ROI to Maximize the Impact of Data and Analytics

Data and analytics ROI strategy is based on the business problem being solved and agreed-upon value being generated.

Analyst Perspective

Missing out on a significant opportunity for returns could be the biggest cost to the project and its sponsor.

		This research is directed to the key decision makers tasked with addressing business problems. It also informs stakeholders that have any interest in ROI, especially when applying it to a data and analytics platform and practice. While organizations typically use ROI to measure the performance of their investments, the key to determining what investment makes sense is opportunity cost. Missing out on a significant opportunity for return could be the biggest cost to the project and its sponsor. By making sure you appropriately estimate costs and value returned for all data and analytics activities, you can prioritize the ones that bring in the greatest returns.
Ibrahim Abdel-Kader Research Analyst, Data & Analytics Practice Info-Tech Research Group	Ben Abrishami-Shirazi Technical Counselor Info-Tech Research Group

This research is directed to the key decision makers tasked with addressing business problems. It also informs stakeholders that have any interest in ROI, especially when applying it to a data and analytics platform and practice.

While organizations typically use ROI to measure the performance of their investments, the key to determining what investment makes sense is opportunity cost. Missing out on a significant opportunity for return could be the biggest cost to the project and its sponsor. By making sure you appropriately estimate costs and value returned for all data and analytics activities, you can prioritize the ones that bring in the greatest returns.

Ibrahim Abdel-Kader
Research Analyst,
Data & Analytics Practice
Info-Tech Research Group

Ben Abrishami-Shirazi
Technical Counselor
Info-Tech Research Group

Executive Summary – ROI on Data and Analytics

Your Challenge	Common Obstacles	Info-Tech’s Approach
Return on investment (ROI) is a financial term, making it difficult to articulate value when trying to incorporate anything that produces something intangible. The more financial aspects there are to a professional function (e.g. sales and commodity-related functions), the easier it is to properly assess the ROI. However, for functions that primarily enable or support business functions (such as IT and data and analytics), it is a lot harder to apply ROI without misrepresenting its true purpose.	Apples and oranges – There is no simple way to apply the standard ROI formula to data and analytics among other critical functions across the organization. Boiling the ocean – Obsession with finding a way to calculate a perfect ROI on data and analytics. Not getting the big picture – Data and analytics teams suffer a skill set deficit when it comes to commercial acumen. Not seeing eye to eye – ROI does not account for time in its calculation, making it prone to misalignment between stakeholders.	Approach ROI for data and analytics appropriately: Answer the following questions: What is the business problem? Whose business problem is it? What is the objective? Define measures of success based on the answers to the questions above. Determine an appropriate cadence to continuously optimize the ROI program for data and analytics in collaboration with business problem owners.

Your Challenge

Common Obstacles

Info-Tech’s Approach

Return on investment (ROI) is a financial term, making it difficult to articulate value when trying to incorporate anything that produces something intangible.

The more financial aspects there are to a professional function (e.g. sales and commodity-related functions), the easier it is to properly assess the ROI.

However, for functions that primarily enable or support business functions (such as IT and data and analytics), it is a lot harder to apply ROI without misrepresenting its true purpose.

Apples and oranges – There is no simple way to apply the standard ROI formula to data and analytics among other critical functions across the organization.
Boiling the ocean – Obsession with finding a way to calculate a perfect ROI on data and analytics.
Not getting the big picture – Data and analytics teams suffer a skill set deficit when it comes to commercial acumen.
Not seeing eye to eye – ROI does not account for time in its calculation, making it prone to misalignment between stakeholders.

Approach ROI for data and analytics appropriately:

Answer the following questions:

What is the business problem?
Whose business problem is it?
What is the objective?

Define measures of success based on the answers to the questions above.
Determine an appropriate cadence to continuously optimize the ROI program for data and analytics in collaboration with business problem owners.

Info-Tech Insight

ROI doesn’t have to be perfect. Parameters and measures of success need to be agreed upon with the key decision makers.

Glossary

Return on Investment (ROI): A financial term used to determine how much value has been or will be gained or lost based on the total cost of investment. It is typically expressed as a percentage and is supported by the following formula:

Payback: How quickly money is paid back (or returned) on the initial investment.
Business Problem Owner (BPO): A leader in the organization who is accountable and is the key decision maker tasked with addressing a business problem through a series of investments. BPOs may use ROI as a reference for how their financial investments have performed and to influence future investment decisions.
Problem Solver: A key stakeholder tasked with collaborating with the BPO in addressing the business problem at hand. One of the problem solver’s responsibilities is to ensure that there is an improved return on the BPO’s investments.
Return Enhancers: A category for capabilities that directly or indirectly enhance the return of an investment.
Cost Savers: A category for capabilities that directly or indirectly save costs in relation of an investment.
Investment Opportunity Enablers: A category for capabilities that create or enable a new investment opportunity that may yield a potential return.
Game Changing Components: The components of a capability that directly yield value in solving a business problem.

ROI strategy on data and analytics

The image contains a screenshot of a diagram that demonstrates the ROI strategy on data and analytics.

ROI roles

Typical roles involved in the ROI strategy across the organization

CDOs and CAOs typically have their budget allocated from both IT and business units.

This is evidenced by the “State of the CIO Survey 2023” reporting that up to 63% of CDOs and CAOs have some budget allocated from within IT; therefore, up to 37% of budgets are entirely funded by business executives.

This signifies the need to be aligned with peer executives and to use mechanisms like ROI to maximize the performance of investments.

Source: Foundry, “State of the CIO Survey 2023.”

Risks with ROI and data and analytics

Be careful of these pitfalls when applying ROI to data and analytics

Misalignment of expectations
- Unclear priorities – Organizations are still trying to figure out what they want from CDOs and data professionals.
- Misaligned value assumptions – Data and business leaders tend to clash when interpreting insights from data.
- Unrealistic expectations – Leaders face unrealistic time expectations and/or value expectations of initiatives that are being assigned to data and analytics.
Immature Practices
- Non-existent processes in calculating and reporting on value.
- Skill set deficit with data and analytics teams in commercial acumen.
Improper use of ROI
- Identifying what variable or dependency could be hindering the total return.
- Trying to calculate a perfect ROI, especially when there is a cultural expectation for data professionals to have a high degree of accuracy.

“The average tenure of CDOs (Chief Data Officers) is just two to two-and-a-half years.”

– Tom Davenport, Randy Bean, and Josh King, Harvard Business Review

This indicates that CDOs need to demonstrate the value of data and analytics to the business sooner rather than later.

Measures of success

Here are some indicators that the ROI strategy on data and analytics is successful:

Business problem owner satisfaction – Ensure the key decision maker is satisfied as a positive trend in satisfaction is parallel with a positive ROI trend.
Capability maturity – Ensure that the capabilities needed to address a business problem exist and are being developed in order to maximize return.
Payback – Understanding when an investment is paid back can help ensure stakeholders are on the same page.
Meeting business problem success targets – Set up some targets for success in relation to addressing a business problem.
ROI parameter alignment – Set up a regular cadence with key stakeholders to review the ROI parameters on data and analytics.

Potential Measurement Methods:\

Net Promoter Score (NPS); Likert scale; CIO Business Vision Diagnostic
Assess Core IT Processes – Management & Governance Diagnostic
Payback period formula – averaging method:
Payback period formula – subtraction method: )
CEO-CIO Alignment Diagnostic

ROI maturity can be determined by the business problem owner’s behavior

Info-Tech’s Maturity Ladder Framework:

Capability Maturity Level	Business Problem Owner’s (BPO) Behavior	Most Likely BPO ROI Score
1. Innovator:	BPO looks to problem solver to proactively suggest new investment opportunities and ways to enhance existing returns.	Good – Exceptional
2. Business Partner:	BPO looks to frequently collaborate with problem solver whenever possible. Problem solver does not feel the need to validate capability’s value proposition anymore.	Good
3. Trusted Operator	BPO engages with problem solver on a regular cadence in addressing business problems.	Minimal – Average
4. Firefighter	BPO will reluctantly request assistance to help put out fires related to their business problems that they can't put out themselves.	Neutral – Minimal
5. Non-existent capabilities:	BPO will rely on informal requests and dispersed pockets of wisdom throughout the organization.	Disappointing – Neutral

Activity: Data and analytics ROI approach – ROI categories

Use the example below as a reference when a having a discussion with another executive around setting parameters for determining ROI benefit:

Investment Opportunity Enabler Examples

Data and Analytics Capability: Data science and AI
Aligned Strategic Objective: Grow customer revenue through cross-selling and upselling
How Data Science and AI Are Investment Opportunity Enablers: Embedding recommendation algorithms within digital channels that automatically make personalized recommendations for product cross-selling and upselling

Return Enhancer Examples

Data and Analytics Capability: Self-service analytics
Aligned Strategic Objective: Grow customer revenue through cross-selling and upselling
How Self-Service Analytics is a Return Enhancer: Real-time customer insights that support call analysts to better understand customer needs and offer value-add products

Cost Saver Examples

Data and Analytics Capability: Master data management
Aligned Strategic Objective: Grow customer revenue through cross-selling and upselling
How MDM is a Cost Saver: More accurate customer and product master data which support risk mitigation when managing contracts during sales activities

See slide 6 – Glossary for a refresher on ROI category definitions

Activity: Data and analytics ROI Approach - Guide

Input	Output	Materials	Participants
Determine the following in the assigned materials (field descriptions are on the following slide): Business Partner Aligned Strategic Objective ROI Category Data and Analytics Capability Problem/Solution Contribution Value Game-Changing Component BPO Dependency Conversation BPO ROI Score Priority Outcomes/Value Measurables	Aligned ROI approach between key decision makers and data and analytics Increased likelihood of a maximized returns on investments	Data and Analytics Service to Business ROI Map	Business problem owners – (e.g. CRO, CMO, CHRO) Problem solvers – (e.g. CDO, CAO)

Input

Output

Materials

Participants

Determine the following in the assigned materials (field descriptions are on the following slide):

Business Partner
Aligned Strategic Objective
ROI Category
Data and Analytics Capability
Problem/Solution Contribution Value
Game-Changing Component
BPO Dependency Conversation
BPO ROI Score
Priority
Outcomes/Value Measurables

Aligned ROI approach between key decision makers and data and analytics
Increased likelihood of a maximized returns on investments

Data and Analytics Service to Business ROI Map

Business problem owners – (e.g. CRO, CMO, CHRO)
Problem solvers – (e.g. CDO, CAO)

ROI field descriptions

Refer to the following descriptions below when populating the following fields mentioned in the activity on the previous slide:

Business Partner	Aligned Strategic Objective	ROI Category	Data & Analytics Capability	Problem/Solution Contribution Value
The key business stakeholder you are building a partnership with and with whom you want to create an agreed-upon set of success measures for D&A services	The high-level strategic objective that the business stakeholder is accountable for delivering and that the D&A initiative/service outcome and value will help achieve	The high-level category for ROI delivery (return enhancer, cost saver, and investment opportunity enabler)	The data and analytics capability/initiative that will enable the value to be realized	How the data and analytics service/initiative will directly contribute to the strategic value being driven
Game-Changing Component	BPO Dependency Conversation	BPO ROI Score	Priority	Outcomes/Value Measurables
What's the key high-value component of the data and analytics service/initiative that is providing the most business value?	What is the business process dependency that the D&A initiative is reliant upon to be successful, and what actions does the business problem owner need to execute to support the D&A initiative’s success?	Indicative ROI score based upon high-level estimate of cost and time to produce versus value generated. All costs/benefits to be accurately qualified and presented to business partner for approval as part of initiative planning	Priority of data and analytics initiative based upon indicative ROI for the BPO	What are the business outcomes to be achieved and what are the SMART measures used to determine if those outcomes are achieved/on track to be achieved?

Insight summary

Don’t miss the big picture. Focus on delivering value, not the ROI score itself
data and analytics ROI strategy is based on the business problem being solved. The ROI score itself doesn’t have to be perfect. Parameters and measurements of success need to be agreed upon with the key decision makers.

Don’t let a missed opportunity become a regret
Missing out on a significant return opportunity could be the biggest cost to the project and its sponsor.
By making sure you appropriately estimate cost and value return for all data and analytics activities, you can prioritize the ones that return the most value.

Payback helps when you have to look back
Payback is a complementary metric to track alongside ROI to help ensure stakeholders are on the same page. It can be used to help with financial planning and assessing risks.

No time to mess around
CDOs need to demonstrate the value of data and analytics to the business sooner rather than later.

The taster’s opinion matters more than the chef’s
Ultimately, business leaders don’t trust anyone’s perception of value and return more than their own. Inaccurate value assumptions, either overinflated or undertested, will create discrepancies between business expectations and what data and analytics will deliver.

ROI maturity can be determined by the BPO’s behavior
As a data and analytics executive, you’ll know if you truly have a seat at the table and are a valued business partner if you don’t feel the need to validate the existence of data and analytics capabilities and business leaders seek you out for collaboration.

Related Info-Tech Research

Understand the Data and Analytics Landscape

The data and analytics landscape comprises many disciplines and components; organizations may find themselves unsure of where to start or what data topic or area they should be addressing.
Organizations want to better understand the components of the data and analytics landscape and how they are connected.

Build Your Data Practice and Platform

Walking through a book of architecture building plans with a personal guide is cheaper and faster than employing an architect to build and design your home.
Data platform design based on Info-Tech data architecture reference patterns and prioritized data initiatives and capabilities.

Mandate Data Valuation Before It’s Mandated

Every organization must calculate the value of their data. This will enable organizations to become truly data driven.
Too much time has been spent arguing different methods of valuation. An organization must settle on valuation that is acceptable to all its stakeholders.
Align data governance and data management to data valuation. Often organizations struggle to justify data initiatives due to lack of visibility in data valuation.

Research Contributors and Experts

Ibrahim Abdel-Kader
Research Analyst | Data & Analytics
Info-Tech Research Group

Andy Neill
Associate Vice President | Enterprise Research; Technical Counselor
Info-Tech Research Group

Chris Dyck
CFO Technical Counselor
Info-Tech Research Group

Ian Mulholland
Research Director | Security
Info-Tech Research Group

Ben Abrishami-Shirazi
Research Director | Data & Analytics
Info-Tech Research Group

Steve Willis
Practice Lead | Data & Analytics
Info-Tech Research Group

Sherwick Min
Principal Research Director | Enterprise Architecture
Info-Tech Research Group

Yatish Sewgoolam
Associate Vice President | Research Agenda & Product Management
Info-Tech Research Group

Amanda Harrison
Executive Counselor | Executive Services
Info-Tech Research Group

Anonymous Contributors

Bibliography

AirOps Team. “How to Measure the ROI of Data Analytics in Your Company.” AirOps, 15 Dec. 2022.
Bean, Randy; Davenport, Tom; and King, Josh. “Why Do Chief Data Officers Have Such Short Tenures?” Harvard Business Review, 18 August 2021.
Beattie, Andrew. “How to Calculate Return on Investment (ROI).” Investopedia, 11 August 2022.
Bechini, Nader; and Salmeen, Najem. “Measuring the Business Impact & ROI of L&D Programs.” ROI Institute, 24 Oct. 2022.
ELEKS. “Data ROI: How to Estimate the Value of Your Data & Analytics Projects.” Medium, 11 Nov. 2022.
Hammel, Matt. “How to Increase the ROI of Your Data Stack.” AirOps, 03 Nov. 2022.
Heidmann, Lynn. “Calculate ROI for Data Analytics & AI Initiatives.” Scaling AI, 18 April 2018.
“How to Estimate ROI and Costs for Machine Learning and Data Science Projects” Altexsoft, 05 July 2019.
Looi, Kelvin. “ROI for MDM.” Mastech Infotrellis, 15 April 2020.
Moses, Barr; and Saxena, Barkha. “How to Measure the ROI of Your Data Organization.” Monte Carlo, 13 Dec. 2022.
“Return on Investment: The Ultimate Guide” TransparentChoice, Accessed Feb. 2023.
“ROI Methodology.” ROI Institute, Accessed Feb. 2023.
“State of the CIO Study 2023 – CIOs Cement Leadership Role.” Foundry an IDG, Inc. company, Accessed Feb. 2023.
Tacoronte, Santiago. “5 Ways to Measure the ROI of Data & Analytics (The Simple Way).” Medium, 17 Feb. 2022.
Tincher, Laurel. “How to Calculate the Payback Period: Formula & Examples.” SoFi Learn, 25 June 2021.
“The 2023 State of IT – SWZD’s Annual Report on IT Budgets and Tech Trends.” SWZD, Feb. 2023.

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