Show Me the Money: A DM/BI Business Value Primer

By
  • Bob Lambert, Tri Truong
Published
  • March 13 2009, 3:40pm EDT

Among data warehousing and business intelligence practitioners, there seems to be a prevailing view that the most important DM/BI benefits are intangible and possible to quantify only after a costly BI effort achieves success. Business cases for DM/BI often rely on vaguely specified better future conditions and hope that an executive sponsor [can] envision the value of the program.1

Even so, by now there are well-documented instances of companies with market dominance directly attributable to DM/BI effectiveness. Shareholders of companies like Amazon.com, Harrah’s and Wal-Mart would agree that DM/BI systems have delivered very tangible benefits over the past decade.

So what do you do if it is your job to write the business case for a new BI effort, with the responsibility for recommending and estimating the outcome of a major BI expenditure?

Follow this step-by-step primer for the BI advocate in a large organization as well as a suggested process that sets the stage for a BI business case, including likely tangible benefits.

Business Value Basics

We’ll start with these basic assertions:

  1. Intangible benefits don’t count.
  2. DM/BI has no inherent value.
  3. Senior managers often make decisions about future outcomes with insufficient data.

Intangible benefits don’t count. An effective business case communicates tangible future value in a convincing way. An argument has a chance of convincing a skeptical reader if the reader agrees that argument’s assumptions are reasonable and that the conclusion follows logically from the assumptions. Quantifying financial metrics like ROI or net present value help build the case, but such measures are credible only if readers agree with the underlying assumptions and the logic built upon them.

DM/BI has no inherent value. We in the DM/BI field believe that any organization’s fortunes would improve if it integrated data rationalized data stewardship, and applied analytics creatively. However, that view must ring true to senior business managers. Without a compelling and motivating story about how a new system contributes to revenue or reduces costs a business case stops dead in its tracks. Sometimes someone at a high level just wants BI, but organizations don’t often embark on DM/BI efforts without first evaluating tangible costs and benefits.

Senior managers make decisions about future outcomes with insufficient data. Although DM/BI practitioners must make a convincing case for future business value, there’s room for uncertainty. Executives and senior managers aren’t highly compensated for playing it safe, but rather for understanding current conditions and setting direction based on educated but sometimes courageous predictions of future conditions. A successful DM/BI business case matches or extends the executive’s knowledge of current conditions and expands his or her view of potential future outcomes of near-term actions.

The Value Foundation of the BI Business Case

Before starting the BI business case, the DM/BI advocate should do the homework required to ensure its success, including these essential steps:

  1. Know the organization’s goals and objectives.
  2. Identify a BI champion.
  3. Identify and work with BI stakeholders.
  4. Identify an application with tangible business value.
  5. Define and quantify a quick win prototype project.

Know the organization’s goals and objectives. It is human nature for any of us, including executives, to be receptive to help with our own goals and objectives but less receptive to new ideas that aren’t related to our own goals. Furthermore, senior executives facilitate intensive strategic planning processes to set the right corporate goals and objectives. A proposed DM/BI initiative should clearly and tangibly help achieve strategic objectives already in place.

Identify a BI champion. BI is in a unique position within the application stack. Most organizations can operate without a DM/BI strategy. However, most companies would greatly improve their market position with a comprehensive DM/BI solution. The impetus for deploying such a solution needs to come from a leader within the corporation who champions the value that DM/BI brings to the organization as a whole. Often, this champion is someone at the top level of the business chain of command with a solid grasp of the BI’s potential.

Identify and work with BI stakeholders. BI projects should be driven by BI stakeholders, those who will see direct effects (good or bad) from the BI project. Some stakeholders look to benefit from BI-based solutions to concrete problems. Other stakeholders will have to be convinced about the potential value of BI. Both types of stakeholder must be involved in defining and supporting the goals of a BI project.
 
Identify an application with tangible business value. Again, in order for the BI application to return value, it must focus on achieving business goals. These goals should be measurable so that the value of the BI application can be determined, and the application should contribute to overall organizational strategy. The next section provides ideas for identifying such a project in your organization.

Define and quantify a quick win prototype project. Businesses must quickly see the value that DM/BI brings in order for it to catch fire in the organization. A prototype project is often the best way to showcase BI’s value proposition. These projects should typically produce tangible results in a matter of weeks and target a well-defined business area. The prototype should have a well-defined goal and ROI metric, and produce data or case studies that show progress toward, if not achievement of, that goal.

Business Value Examples

The references available on DM/BI value cite many BI success stories with tangible value. Analysis of those success stories reveals that BI value tends to fall into these categories:

  1. Enhancing the value of existing assets,
  2. Improving customer or supplier value and
  3. Generating revenue from data assets.

Although it is impossible to predict the real outcome of a BI effort, this section offers a way to estimate benefits of a future DM/BI initiative.
Enhancing the Value of Existing Assets

Some innovative BI applications deliver value by providing insights into lost opportunity in utilizing existing resources. These efforts, most often working hand in hand with business process redesign, may include replacement of outdated reporting systems, automation of previously manual reporting systems, or enabling better monitoring and adjustment of an existing process.

Examples:

  • One comparative analysis of home improvement stores Lowes and Home Depot attributes Lowes’ mid-decade market advantage to BI. “Lowe's uses ‘planograms’ – data-driven shelf plans – to influence where and at what level it puts every product it sells. The goal: Move big projects and all the goods that go with them…Analytical software helps check which [products] generate the most profit, where they get the best attention and what season gets the most action. The results are run through a series of rules… [and] out comes a floor and shelf plan.”2
  • Welch’s has been able to leverage BI in its shipping operations to improve transportation efficiency and provide insight into operational costs. 3 Using its BI system, Welch’s is able to maximize the capacity of its truckloads and level-set its delivery schedule so that approximately the same number of trucks are used daily. The BI system also provides a historical view into its carrier cost structures including fuel surcharges and unloading fees, providing pertinent data when negotiating rates with carriers.

Follow these steps to building the value proposition for bi-supported enhancement of existing assets:

  • Identify your organization’s core business processes.
  • Subjectively evaluate potential cost and value improvements by evaluating process cost against competitors (if data is available). Talk with operations and management staff, and review job aids and process manuals to learn how core processes work. Talk with IT application developers who support operational systems involved in the business process to obtain further insight.
  • Model process flow, emphasizing. Changes in object status and attribute values as objects pass through the process; likely bottlenecks, delays and other inefficiencies; and key measures that can be used to gauge cost reductions.
  • Based on the process model, hypothesize potential improvements. Out of the list of potential improvements, identify those that will result in the most ROI.
  • Explore avenues for leveraging the data available from the BI system for additional value-add. One collections organization leveraged their data warehouse for both internal and external clients, providing clients with timely insight into how their accounts were being serviced. The BI system became a primary selling point for the collections organization.
  • After implementing process improvements, continue to monitor and measure key metrics in order to gauge the effectiveness of your actions. Integrate into processes a feedback loop to enable continuous measurement and process improvement. Companies may utilize a business process management system integrated with BI to facilitate this cycle. 4

Improving Customer or Supplier Value

Supply chain management and customer relationship management systems are specialized DM/BI applications focused on suppliers and customers, respectively. Organizations have deployed BI solutions to reduce supply and delivery costs and increase the value of customer and supplier portfolios. Research shows that organizations that can detect and disseminate information about supply chain disruptions can reduce the severity of the disruption through the expeditious application of corrective measures.5 BI can therefore serve as a risk mitigation measure.

Examples:

  • The Royal Bank of Canada uses a marketing data warehouse to determine the profitability of customers. 6,7 Using this profitability data, the bank can then create micromarkets to offer an individual product line for different customers through the various channels available (such as direct mail, telephone solicitation and personal calls). This targeted marketing allows branch managers to make better informed decisions and relieves stress on the customer since the products available to the customer have been predetermined. Finally, the RBC uses its customer information to determine the level of service that a customer should receive. More profitable clients receive more prompt service and are directed toward specific customer service representatives.
  • Credit card fraud costs the financial services industry approximately $4.84 billion in 2007, or 4.8 cents per $100 in total volume. 8 In light of this, HSBC implemented a fraud detection BI system to improve fraud detection rates and therefore strengthen customer protections. 9 Because the system reduced the number of false positives, the likelihood that customers would be contacted erroneously was reduced. The new BI system also had the side benefit of reducing the computing resources needed for fraud detection by 30 percent.

Follow these steps to the value proposition for improving customers or supplier value:

  • Determine the contact points between your business and your customer and supplier base.
  • Identify the data that you collect (or will potentially collect) that relates to your customer or supplier base. Most of this data will reside in CRM, SCM or enterprise resource planning systems, but new data collection mechanisms may need to be put in place based on your analysis (part of the cost side of the business case).
  • Analyze the data collected to define metrics of customer/supplier value and thereby identify the data elements that help determine their value.
  • Identify opportunities to influence the values of the metrics defined above, and thereby improve efficiency and reduce risk to your business. This may involve creating a strategy for mining the data that is available and then using this mined data to improve business processes (see enhancing the value of existing assets previously explained).

Generating Revenue from Data Assets

Increasingly, companies are finding that the data they gather is a commodity in and of itself. Data can be used internally to expand market share, in product segmentation analysis, market analysis and predictive analysis. Companies that utilize the data effectively to make fact-based decisions are at a competitive advantage to those that don’t. 10 Furthermore, examples abound of companies whose business models revolve around selling data (Nielsen, Arbitron, Bloomberg).

Examples:

  • Eneco Energie, a Dutch utility company, was able to increase its customer base in an increasingly open and competitive environment by utilizing customer insights exposed by a new BI system. 11 Because the Dutch electricity and gas markets were converted from location-based to open markets, Eneco’s customer base was in constant flux. Eneco was able to derive a competitive advantage from its BI solution by allowing its business sector to drive the data reporting goals.
  • “Established in 1988, Capital One emerged as a Fortune 500 company within a decade by aggressively growing its credit card service through an analytical, data-centric approach that helped grab credit card market share and slash its costs. Following its success in the credit card market, it has branched out to become a major player in retail banking, auto finance, mortgage lending and other financial services.” 12

Follow these steps to building the value proposition for generating revenue from data assets:

  • In a short, time-boxed effort, create a high-level conceptual data model identifying the data collected and managed by your organization.
  • Using the resulting data model, identify data with potential market value and low risk of compromising competitive position or customer/supplier privacy. In order to address privacy, the data may need to be secured through implementation of an authentication mechanism and/or scrubbed of personal information.
  • Research the competition and marketplace. Take advantage of existing relationships with customers and vendors to survey their needs.
  • Through brainstorming, identify avenues where BI can facilitate increasing market share or expansion into new markets. Again, utilize customers and vendors to provide input. Provide an avenue for external feedback to be analyzed in conjunction with internal opinions.
  • Estimate the value of the data assets and the costs of making that data available to the market. Be sure to include the costs for securing the data to comply with privacy standards.

References:

  1. Quotes in this paragraph are from Frank Brooks, Senior manager of data resource management and chief data architect, BlueCross BlueShield of Tennessee, in Business intelligence ROI: Five keys to justifying BI investments, Hannah Smalltree, http://SearchDataManagement.com, 02 Mar 2007, at http://searchdatamanagement.techtarget.com/originalContent/0,289142,sid91_gci1245954,00.html accessed 11/11/07.
  2. Lowes’ Big Plan, Larry Dignan, 6/16/2003, http://www.baselinemag.com/print_article/0,3668,a=43244,00.asp accessed 11/11/07. 
  3. Welch's leverages BI to reduce transport costs, 10/16/2008. http://weblog.infoworld.com/sustainableit/archives/2008/10/welchs_oco_bi.html accessed 11/24/2008.
  4. Williams, Nancy, Achieving Business Intelligence Impact: Integrating Business Intelligence With Core Business Processes. http://www.b-eye-network.com/view/6283 accessed on 1/9/2009.
  5. Business Intelligence - a key element in Supply Chain Risk Management, 11/16/2008. http://husdal.com/2008/11/16/business-intelligence-supply-chain-risk-management/.
  6. The New Data Warehouse Business Opportunity: Regenerating Revenues and Increased Profitability through Knowledge Convergence, Ronald S. Swift. http://www.tdwi.org/publications/display.aspx?id=6036 accessed 11/24/2008.
  7. Customer Profitability and Customer Relationship Management at RBC Financial Group (Abridged), V. G. Narayan. http://www.csb.uncw.edu/people/howe/classes/MKT445/SUM%20I%2008/customer%20profitability%20&%20crm%20at%20rbc.pdf.
  8. The Nilson Report July 2007, Issue 884, http://www.nilsonreport.com/issues/2007/884.htm accessed 11/24/2008.
  9. SAS Improves Fraud Protection for HSBC, 11/31/2007 at http://www.sas.com/news/preleases/103107/hsbcfraudprotection.html accessed 11/24/2008.
  10. Prof. Tom Davenport's Research Sees Business Intelligence Emerging As Crucial Competitive Advantage, 04/12/2005. http://www3.babson.edu/newsroom/releases/davenportsas.cfm accessed on 11/24/2008.
  11. BI Tools Power Utility Giant's Rise, 03/24/2005. http://www.intelligententerprise.com/showArticle.jhtml?articleID=159905608 accessed on 11/24/2008.
  12. Capital One Financial, http://www.wikinvest.com/stock/Capital_One_Financial_(COF), accessed on 12/17/2008.

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