Calculating the ROI of EII: Developer Productivity (Example 3/5)

With this entry, we'll move from the business side of the house to the development side of the house.  Yes, EII has something for everyone.

Recent IDC research reports that the average enterprise spends 40% of its IT budget on data integration (ETL, EII, EAI, etc.). Custom programming to connect disparate data sources is expensive to develop and maintain, especially in an environment of continual change. The unified abstraction layer that EII provides allows developers to write to one common interface to access multiple data sources, reducing the total development effort for new applications. The ability to write queries and not code allows departmental control of data integration, which saves the time and effort of going through a corporate IT group. These queries can be reused among different groups, further saving money.

So, What percentage of your IT budget do you spend on data integration tasks?   There are two ways to look at it.

                             

Top-Down Approach	Example	Formula
Annual IT budget ($)	$10,000,000	A
% spent on integration (%)   (ETL, EAI, EII, etc.)	40%	B
% improvement with EII (%)   (estimate)	10%	C
Potential annual cost savings   from EII ($)	$400,000	(A * B) * C

In this example, a company with a $10 million IT budget would save $400,000 annually (4% of overall IT budget) by including EII in their overall data integration strategy.

 

                                                           

Bottom-Up Approach	Example	Formula
Number of developers on   integration projects	20	A
Annual cost (including   benefits) of developers ($)	$120,000	B
% improvement with EII (%)   (estimate)	10%	C
Potential annual cost savings   from EII ($)	$240,000	(A * B) * C
Person-weeks for integration   projects over a year	1,000	D
Annual cost (including   benefits) of developers ($)	$120,000	E
% improvement with EII (%)   (estimate)	10%	F
Potential annual cost savings   from EII ($)	$240,000	(D * (E / 50)) * F

In these examples, a 20-person team would save $240,000 annually using EII as a part of their data integration projects.

And, as usual, some additional upside potential:

• What creative revenue generating or cost reducing functions will your team develop in the time they save by not rewriting software to accommodate changes in infrastructure or data format?
• How much more productive will your developers be if they focus on writing interesting applications rather than on more basic data integration tasks?

All for now.

Calculating the ROI of EII: Analyst Utilization (Example 2/5)

Here's one of my favorites, inspired by a conversation we had with a prospect back in 2005.  It's a great product management moment when the benefits of your product dovetail so nicely with a problem a customer has.

To wit, a vice president at a commercial bank that did not use EII told us that the analysts there spend about 60% of their time on data collection and only 40% on analysis. Moving from a 40%-60% split to a 90%-10% split means more than doubling (125%) individual analyst productivity. Thus, one analyst can do the work of slightly more than two. EII allows analysts to simplify the data collection process and spend more time producing useful, actionable information.

So, here's the question to unlock your potential ROI: How much time do your analysts spend searching for data?

                                   

	Example	Formula
Percentage of   time analysts spend on value-added activities pre-EII (%)	40%	A
Percentage of   time analysts spend on value-added activities post-EII (%)	90%	B
Number of   analysts on your team	10	C
Annual cost   (including benefits) of analyst ($)	$100,000	D
Potential annual   cost savings from EII ($)	$555,556	((B - A) / B)   * C * D

In this example, a team of 10 analysts does about 20 person-days of analysis per week pre-EII and 45 person-days per week post-EII, for a 125% improvement. If the amount of work was fixed at 20 person-days per week, a team of 5 analysts (actually 4.44) could do the job that previously required 10.

Additional Upside

Still need more ammo?  Think about quantifying these:

· What new discoveries will your analysts make when they have more time to focus on analysis?

· How many errors will be eliminated by reducing manual handling of data and what will the cost savings be of eliminating these errors?

· By spending more time using data rather than looking for it, how much more valuable will the analysts become to the organization?

· What is the effect on job satisfaction if people are doing what they enjoy, rather than just collecting data?

That's it for this installment.  Three more to go.  Stay tuned.  If you can't wait, check out the complete ROI guide, which can be found in Ipedo's EII Zone.

Calculating the ROI of EII: Increased Flexibility (Example 1/5)

As we move into the planning and budgeting season, the time seems right to start talking about ROI.  At Ipedo, we've spent quite a bit of time analyzing how our customers can save money and improve productivity using EII.  In this five-part series, I'll show you how to do it.

What kicked off our study of the financial benefits of EII was a 2005 study by The Data Warehousing Institute (TDWI).  In it, 69% of respondents said that data integration issues are a barrier to implementing new applications. The three main issues they listed were poor data integration infrastructure, lack of a business case and inadequate funding, and data quality and security.

This series will help decision makers responsible for data integration projects develop a business case that quantifies the potential cost savings of an EII project based on their organization’s specific information integration needs.  Each installment will focus on a specific area where EII can generate cost savings and productivity improvements:

• Increased flexibility to respond to changes in IT requirements
• Better analyst utilization
• Higher developer productivity
• Lower data consolidation costs
• Less expensive application maintenance

A few housekeeping items before we start.  In the  scenarios, we provide examples to illustrate the potential cost savings. Each example is for a departmental EII implementation, as opposed to an enterprise-wide deployment. Most organizations start with a single use for EII and then scale it to different departments once they achieve their target results and become comfortable with the technology.

The cost savings numbers represent the ongoing annual savings, after the initial cost of implementing the EII system. This cost of an EII system will vary, depending on your specific needs. For the departmental-scale examples in this document, a 1- or 2-CPU system with matching failover server will be sufficient in most cases. A complete Ipedo deployment for a scenario, including software license, maintenance, training, and some customization through our professional services group will cost around $200,000. A bare-bones EII system can cost as little as $50,000.

Your savings may be higher or lower than what we illustrate, depending on your specific use case and the cost of implementing your EII solution. To simplify testing different scenarios, running your own numbers, and performing “what if” analysis to determine your own cost savings, Ipedo has a companion Excel worksheet. If you are interested, let me know and I can send you a copy.

So, with all that out of the way, let's get down to brass tacks and look at how Ipedo can save you money by increasing flexibility in a reporting application.

Increased Flexibility in Reporting

In today’s information economy, having access to data across the enterprise gives managers and executives a significant advantage in making real-time decisions that affect their business. EII allows companies to respond quickly to changes in market conditions without incurring a major IT investment.

What effort is involved to link new data sources to your existing reports or applications?

	Example	Formula
Conventional Approach
Cost to modify a report to integrate a new data source ($)	$1,000	A
Number of changes required annually	200	B
Cost to modify an application to integrate a new data source ($)	$5,000	C
Number of changes required annually	50	D
Reporting cost using conventional approach ($)	$450,000	(A * B) + (C * D)
EII Approach
Cost to modify a report to integrate a new data source ($)	$100	E
Number of changes required annually	200	B
Cost to modify an application to integrate a new data source ($)	$0	F
Number of changes required annually	50	D
Reporting cost using EII approach($)	$20,000	(E * B) + (F * D)
Potential annual cost savings from EII ($)	$430,000	(A * B) + (C * D) - (E * B) + (F * D)

In this example, a business unit that modifies four reports and one application a week will save $430,000 by using EII.

Additional Upside

These are a few soft benefits.  You can either try to assign a value, or you can just treat these as icing on the cake.

• By getting useful information sooner, what is the value to your organization?
• What new insights can your managers discover by having access to a unified view of disparate information that EII provides?
• As new regulations appear, how quickly can you respond to generate the necessary documentation? What is the burden on your organization to create these reports? Whose budget covers producing regulatory reports?

That's all for now.  I'd be curious to hear back on how people think these numbers match their own situations.

Stay tuned for our next installment.