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Now is the Time: An ROI for Business Intelligence

Originally published April 28, 2009


It’s become a bit of a cliché for 2009, but during these “turbulent economic times,” we need to be able to show the return on investment for business intelligence (BI) deployments. Return on investment (ROI) has been very elusive for the BI industry. The conundrum is that most companies understand at a very intrinsic level that organizing data and providing access to information has value. They have historically supported business intelligence based on that assumed intrinsic value. But with the inevitable budget-slashing, business intelligence is on the short list because an effort has not been made to validate the objective value of the data. When these efforts have been made, the difficulty comes in getting to a positive ROI because enterprise BI projects can be very expensive. In addition, quantifying the value of things like faster reporting and more productive users is a real challenge. This article will review the ROI analysis for business intelligence and provide tips on finding the hidden value of business intelligence in your organization, measuring the intangible aspects of BI, and positioning the discussion on value in the context of investment. As a result, you will be better prepared for the day when your CFO asks you to demonstrate the ROI of your BI program.

FYI: CBA, IRR, NPV, ROI

Defining variations on the theme of ROI is important. Aspects of the net present value (NPV) and internal rate of return (IRR) can be used in an ROI calculation. For some companies, it is possible to replace the cost benefit analysis (CBA) for the ROI, making your work that much easier.

In finance, ROI is the ratio of money gained or lost on an investment relative to the amount of money invested. Cost benefit analysis (CBA) is a formal discipline used to help appraise or assess the case for a project or proposal, weighing the total expected costs against the total expected benefits.

Net present value (NPV) is defined as the total present value of a time series of cash flows. It is a standard method for using the time value of money to appraise long-term projects.

The internal rate of return (IRR) is a capital budgeting metric used by organizations to decide whether they should make investments. It is an indicator of the efficiency or quality of an investment, as opposed to NPV, which indicates value or magnitude.

Step-by-Step Approach to Calculating ROI

If you can’t complete your ROI analysis in five steps or less, then you should do an ROI analysis on your ROI analysis. The faster you are able to put a stake in the ground regarding the quantifiable value of your program, the faster you can get to proving it, the most valuable aspect of the analysis.

Step 1: Define the Business Goals in Terms of Success

Simply stated, a goal is any request by the business that can be supported by an enterprise data warehouse through a business intelligence layer. Although this is a very broad definition, a true enterprise BI program should deliver business value to all aspects of the organization. As you define each goal, state it in terms of success, such as “Provide the Appeals Department a personalized portal with pre-defined reports.” If creation of this portal and its reports will make the Appeals Department more productive, then you have used success criteria in defining your goal.

Step 2: Quantify the Goals

Before you can measure a goal, you need to define it in terms that are measurable. Using the example of the Appeals Department portal, the measurement of this goal will be the availability of the portal, how active the portal is, and how many pre-defined reports have been run. If your first thought is to define a goal as “Improve Customer Satisfaction,” stop and think how it will be measured later, and change it to “Improve Customer Satisfaction by 1% each quarter, for a cumulative change of 4% for the year.” This way, as each quarter passes, you can measure your progress and avoid any unhappy surprises at the end of the year. This also allows you to make a mid-year course correction if things aren’t going as planned – you could restate the goal or revise the survey that measures the satisfaction.

Step 3: Calculate the ROI

Once you have all the data, calculating the ROI percentage is easy. Simply apply the data to the calculation.

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Step 4: Program Evaluation

Set up a plan to consistently measure and validate the ROI analysis. Critically important in determining the long-term value of the program is periodically reviewing your ROI analysis and seeking to improve it through better goal definition, improved metrics, etc. Your organization’s vision and mission are not stagnant and your ROI analysis shouldn’t be either.

The Intangibles: Measuring the Value of Soft Return on Investment

Often referred to as the soft aspect of an ROI analysis, the intangibles will likely determine the difference between positive and negative ROI for your program. The trick here is to make the unmeasurable measurable. Every intangible metric has some aspect that is quantifiable. You may have to break it down into a smaller piece of consumable data, but somewhere there is a metric that can be measured.

We all know the value of goals such as faster reporting, better management information, better decision making, more productive users, improved customer satisfaction, faster decisions, opportunity cost, efficiency gains and better customer segmentation. The challenge is measuring them so that your executives do not question your methodology or analysis. In a recent conversation with a CFO about an ROI analysis that I had completed, he questioned my methodology, specific to a calculation I had made attributing a percentage of sales to the BI program. The calculation made my ROI positive; without it, it was negative for more than a three-year period. Even though I had discounted the value of the intangible metric (we only allocated 2% of a sale) and had validated the assumption with the VP of Sales, backed by our Lost Sales Surveys, it was still removed from the calculation. You must not only quantify whatever you can, but have a strong business case behind including it in the calculation. Even then, you may not convince everyone.

Some goals are easier to measure than others. For example, creating a survey to measure your customer satisfaction and how it fluctuates is reasonably straightforward. But remember that when designing the survey, everyone must agree about the impact a BI program has on customer satisfaction so that the survey answers will produce the metrics you’ll need later.

A goal like better decision making, however, is a more amorphous concept. “Good decisions usually have systematically assembled data and analysis behind them” (Davenport & Harris,Competing on Analytics, Harvard Business School Press). It’s still difficult to measure the cost of a bad decision, or compare it to the value of a good decision. Only with proper use of your organization’s business intelligence are you able to quantify the value an informed decision delivers. For example, if you enter a new market, you are able to analyze the metrics associated with that exercise in order to make a more informed decision as well as measure the result of that decision – i.e., the increase in revenue, improved market penetration, etc. With that said, it is still best practice to discount the impact of the intangibles between 10-40%. This risk adjustment provides the opportunity to include these important factors in your analysis without putting your investment at risk (www.tompiselloroiguy.blogspot.com, March, 2009).

Opportunity Cost

Opportunity cost is the most under-considered aspect of ROI for BI programs and, arguably, the most noteworthy benefit of business intelligence. There is no question that in certain industries access to data or ability to provide access to data is a major competitive differentiator. “BI is a sustainable competitive advantage. It allows the organization to drive revenues, manage costs, and realize consistent levels of profitability. An ‘intelligent enterprise’ – one that uses BI to advance its business – is better able to predict how future economic and market changes will affect its business. Such an organization is able to adapt to the new changes in order to gain.” (Bogza, R.M.; Zaharie, D.,Automation, Quality and Testing, Robotics, 2008. Volume 1, Issue, 22-25 May 2008, pages:146 – 151.) Your organization’s ability to manage a BI program could mean the difference between losing customers and gaining them – a very quantifiable metric!

 
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The Hard Truth

The easiest parts of an ROI analysis are the tangible measurements like the cost of hardware, software and full-time equivalents (FTEs). You may be able to find a couple of tangible benefits for your ROI calculation such as the reduced cost of software (if you switch pricing models or just software itself). Reduced FTE is a benefit to your bottom line. If you can’t (or are not willing) to reduce FTE, you may also see a benefit in reducing the pedestrian tasks of preparing data so those same FTEs will have time to complete value-add analytics.

A Plan of Action

To take full advantage of an ROI analysis, first define your business goals, making sure to consider the entire enterprise your program serves. Once your business goals are stated, you must plan to measure against them. In order to do this, make sure you take into account both the tangible and intangible elements of the goal. For the intangible elements, consider breaking them into smaller, more measureable metrics. Finally, actively manage the analysis and metrics and run the analysis twice a year. As your business grows and your metrics change, make sure to adjust accordingly.

2009 will be the year of the ROI. The days of getting your BI program funded based on the assumed value of managing data are gone. As a BI practitioner, it is your responsibility to complete a comprehensive ROI analysis. You will need to be prepared to defend your program.



  • Laura MadsenLaura Madsen
    Laura leads the healthcare practice for Lancet, where she brings more than a decade of experience in business intelligence (BI) and data warehousing for healthcare, and a passion for engaging and educating the BI community.  At Lancet, she spearheads strategy and product development for the healthcare sector. She also works with key accounts across the country in the provider, payer, and healthcare manufacturing markets. Laura is the founder of the Healthcare Business Intelligence Summit, an annual event that brings together top hospitals, insurers, and suppliers in the healthcare business intelligence space. Laura is also the author of the popular book, Healthcare Business Intelligence: A Guide to Empowering Successful Data Reporting and Analytics (Wiley, 2012). You may reach her at lmadsen@lancetsoftware.com.

    Editor's note: More healthcare articles, resources, news and events are available in the BeyeNETWORK's Healthcare Channel featuring Laura Madsen and Scott Wanless. Be sure to visit today!

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Posted April 29, 2009 by Caleb Decker calebdecker@gmail.com

Good article Laura.

I have found that traditional NPV or similar ROI calculations are near impossible in projects that are not revenue generating. Moreover, our benefit formula, in the simplest form (cost/benefit), suffers from not having solid data on the denominator. Meanwhile we have exact data on the numerator. Cost is easily determined, through licensing costs and consulting fees. But the benefit number can be elusive.

The approach that I have adopted is focusing on the "cost of the problem". We must measure the current state; the business processes, associated labor costs and direct expenses. We can come up with a dollar figure that represents the sum of these costs. If the cost of our BI solution is less than the cost of the problem, then most reasonable business leaders would fast track the project.

The next challenge is gaining adoption such that those processes are improved, the spreadsheets and data silos are eleiminated, and the projected business benefits are realized.

Caleb

Caleb Decker

Healthcare Advisory Services Director

MicroStrategy

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