News Stay informed about the latest enterprise technology news and product updates.

Using ROI calculations to measure the value of your infrastructure

Measuring the value of technology initiatives

This article originally appeared on the BeyeNETWORK

It’s been interesting to watch the financial services industry cycle through the “funding of technology” process.  It seems that every cycle is driven by a burst of new business-side technologies positioned to deliver huge return on investment (ROI).    However, the financial math behind the ROI calculations for infrastructure falls short of delivering the tremendous revenue and/or market share gains of which companies dream. 

Think back on how CRM and the Internet were going to change the foundation of banking by enabling customers to bank anywhere at any time.  Branches would be obsolete and market share would shift to the institutions that delivered customer-centric, electronic access 24/7.  Then the dot-com world brought us the business-to-business (B2B) networks and the on-line auctions that would revolutionize B2B interactions. 

It took an over-heated stock market coupled with the 9/11 attacks to demonstrate the inherent weaknesses in traditional ROI calculations. Let’s take a brief look at these calculations. 

Three key numbers drive traditional ROI calculations:

  • Cost – the initial capital and current expenditures to acquire;
  • Revenue – the incremental gain in revenue per period in next 8 quarters; and
  • Cost Savings – the reduction in annual expenditures this year and next.

Here’s an example of a typical ROI formula for a business-side system like a CRM:

  • Cost = number of licenses + hardware + systems integrator;
  • Revenue = 1% share of wallet increase = hundreds of millions of dollars; and
  • Cost Savings = 0. 

In the “good old days,” cost numbers were generally underestimated, revenue was optimistically overstated, and cost savings were ignored because they were “soft dollars” and hard to measure.  

The focus was all on purchasing: get the cost as low as possible because the revenue potential was awe-inspiring. Very little thought or concern was paid to “messaging, pipes and plumbing” technologies that were required to feed the CRM system.  It was not until   huge failures erupted that institutions realized that installing the software without changing business processes, implementing new strategies and training staff was a recipe for disaster.  

There was an even more insidious lesson taught but not really learned.  Investments in basic data infrastructure were deferred due to the inability to link them with “hard-dollar” revenue flows or “hard-dollar” cost savings. The individual CRM “solutions” came with their own requisite infrastructures.  This required institutions to load source data to feed the packages – leading to tremendous time delays and cost overruns. 

I remember speaking with the CIO of one of the top five US banks. He was ranting over the latest cost increase for a CRM installation.  It seemed that the initial business case assumed interfacing with 14 systems to feed the required customer data.  Fifteen months into the project, a subsequent estimate set the number of interfaces at 137!   All of these were being loaded from the source data. 

Another lesson taught, but not learned, was the value of “the enterprise view.”  CRM systems implemented by individual lines-of-business (LOB) are extremely costly in the long-run as compared to initially taking the entire enterprise into consideration. But this was a time when budgets were LOB-centric and business silos were tall and reinforced.   In other words, financial institutions were loose confederations of independent businesses supported by a network of non-coordinated technology. This was justified by the most complex and overstated revenue-centric ROI formulas ever to emerge from an MBA graduate’s laptop.  

Unrealized business cases supporting billions of dollars of wasted investments, combined with poor management and the lack of infrastructure investments brought front-page exposure for Core States, Enron, World Com, PNC, Fannie, Freddie, Riggs, SunTrust and now Huntington--just to name a few.  The 9/11 attacks exacerbated everything by pointing out the control weaknesses in virtually every aspect of our financial institution infrastructures and payment systems. 

This front-page exposure led to Sarbanes-Oxley, SEC investigations, Basel II, US Patriot Actand in-depth regulatory exams.  These in turn, have led to a new basis for evaluating technology investments.  The newest is: 

Keep us off the Front Page of the Wall Street Journal (KUO(FP)WSJ) 

The key numbers driving KUO(FP)WSJ calculations are:

  • Cost – the initial capital and current expenditures to acquire and install infrastructure;
  • Market Cap Loss – if a problem hits the front page or evening news;
  • Fine – amount charged by the SEC or other regulator for violations;
  • JT – estimated jail time of executive management (if applicable);
  • Revenue – the incremental gain in revenue in the long-run; and
  • Cost Savings – the reduction in annual expenditures in the long run. 

What is fascinating is that the whole trend in the “funding of technology” process is shifting to focus on ENTERPRISE INFRASTRUCTURE versus the business side, revenue-driving, front-end packages.  Across the industry, billions of dollars are being spent to ensure that the enterprise has access to all of the data, and that it can be audited and traced from report to source.  Point solutions for extracting data are giving way to enterprise ETL hubs complete with enterprise repositories for metadata and business rules.  

Executive management is beginning to recognize what the technologists have long known: enterprise data strategies and infrastructures enable greater management controls, better decision-making and ultimately greater revenues in the long term.  

In coming articles, we will further explore the KUO(FP)WSJ  formula and its application in areas like Internal Audit, Basel II, Anti-Money Laundering & Fraud, Operations Risk, Credit Portfolio Management, and Trading Risk.

Dig Deeper on Business intelligence architecture and integration

Start the conversation

Send me notifications when other members comment.

Please create a username to comment.

-ADS BY GOOGLE

SearchDataManagement

SearchAWS

SearchContentManagement

SearchOracle

SearchSAP

SearchSQLServer

Close