InfoGov: Productivity Gains Equal Revenue Gains

A great deal has been written on lost productivity and the benefits of information governance. The theory being that an information governance program will raise employee productivity thereby saving the organization money. This theory is pretty well accepted based on the common sense realization and market data that information workers spend many hours per week looking for information to do their jobs. One data point comes from a 2013 Wortzmans e-Discovery Feed blog titled “The Business Case for Information Governance – Reduce Lost Productivity! that states employees spend up to nine hours per week (or 1 week per month or 12 weeks per year) looking for information. The first question to consider is how much of that time searching for information could be saved with an effective information governance program?

InfoGov Productivity Savings

Three months out of every year spent looking for information seems a little high… so what would a more conservative number be for time spent searching for information? In my travels through the archiving, records management, eDiscovery, and information governance industries, I have spoken to many research analysts and many, many more customers and have generally seen numbers in the 2 to 4 hours per week range thrown around. Assuming the four hours per week estimate, the average employee spends 208 hours per year (26 working days or 5.2 weeks) looking for information. Let’s further assume that an effective information governance program that would capture, index, store, and manage (including disposal), of all ESI per centralized policies would save 50% of the time employees spend looking for information (not an unrealistic estimate in my humble opinion), or 104 hours per year (13 days or 2.6 weeks). To bring this number home, let’s dollarize employee time.

Table 1 lays out the assumptions we will use for the productivity calculations including the average annual and hourly salary per employee.

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Table 2 below shows the calculations based on the assumptions in table 1 for weekly and annual time periods.

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Assuming a work force of 1000 employees at this company, the total annual cost of search is $7.5 million. Assuming a 50% increase in search productivity gives us an estimated $3.75 million saving from recovered employee productivity. In most cases, a $3.75 million annual savings would more than pay for an effective information governance program for a company of 1000 employees. But that potential savings is only a third of the recoverable dollars.

Another productivity cost factor is the amount of time spent recreating data that couldn’t be found (but existed) during search. Additional variables to be used for calculations include:

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Most employees will agree that a certain percentage of their search time is spent looking for information they don’t find…until well after their need has passed. This number is very hard to estimate but based on my own experience, I use a percentage of 40%. The other important variable is the amount of time (as a percentage) spent actually recreating the data you couldn’t find. In other words, the percentage of time (200%) of hours spent searching for information but not finding it (table 3).

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Table 4 above lays out the calculations showing the total hours wasted recreating data that should have been found of 166,400 across the entire company or $6 million. The assumption is that this wasted time spent recreating data not found would be reduced to zero with an effective information governance program.

So far the estimated saving based on recovered productivity (if they adopted an information governance program) for this company of 1000 employees is $3.75 million plus $6 million or $9.75 million (table 5).

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The last (and most controversial) calculation is based on the revenue opportunity cost or in other words; what additional revenue could be generated with a productivity recovery increase in employee hours? For these calculations we need an additional number; the annual revenue for the company. Divide this by the number of employees and you will get the average revenue per employee and the average revenue per employee per hour (table 6).

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How Does Productivity Affect Revenue

The last variable that needs an explanation is the “discount factor for revenue recovery” (table 6). This discount factor is based on the assumption that every recovered hour will not equal an additional (one for one) average revenue per employee per hour. Common sense tells us this will not happen but common sense also tells us that employees that are more productive generate more revenue. So in this example, I will use revenue recovery discount factor of 60% or 40% of the above $101.92 per hour number. This is met to impose a degree of believability to the calculation.

To calculate the total (discounted) recoverable revenue from improved information search we use the following formula: Estimated recoverable productivity hours for wasted search time * (the average revenue per hour per employee – (1 – the revenue recovery discount factor)) or 104,000*($101.92*(1-60%)) which equals $4,239,872 or $4.24 million.

Calculating the (discounted) recovered revenue from productivity gains from recreating data not found we will use the following formula: Estimated total hours spent recreating data not found * (1 minus the revenue recovery discount factor * the average revenue per employee per hour or (166,400*(1-60%)*$101.92) equals $6,784,000.

So to wrap up this painful experiment in math, the potential dollar savings and increased revenue from the adoption of an information governance program is:

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The point of this discussion was to explore the potential of using the concept of recovered revenue from increases in productivity from the more effective management of information – information governance. You may (probably) disagree with the numbers used, but I think the point of calculating an InfoGov ROI using recovered revenue due to productivity gains… is realistic.



The ROI of Conceptual Search

After people, information is a company’s most valuable asset. But many are asking; “what’s in that information?”, “who controls it?”, “can others access it?”, and “is it a risk to keep?”, “for how long?”. The vast majority of information in any organization is not managed, not indexed, and is rarely–if ever–accessed.

Companies exist to create and utilize information. Do you know where all your organization’s information is, what’s in it, and most importantly, can those that need it find and access it? If your employees can’t find when they need it, then the return on investment (ROI) for that information is zero. How much higher could the ROI be if your employees could actually find and share data effortlessly?

Enterprise search – The mindless regurgitation of keyword matches

Enterprise search is the organized query/retrieval of information from across an organization’s enterprise data systems. Data sources include e-mail servers, application databases, content management systems, file systems, intranet sites and many others. Legacy enterprise search systems provide users the ability to query organizational data repositories utilizing keyword-based inquiries that returns huge results sets that then have to be manually filtered by the user until they find what they were looking for (if they actually find it).

A sizeable drawback to a keyword-based search is that it will return all keyword matches even though they may be conceptually different – false positives.

What is conceptual search?

A conceptual search is used to search electronically stored information for information that is conceptually a match or similar to the information represented in a search query as opposed to a keyword search where only documents with exact keyword matches are returned. In other words, the ideas expressed in the information retrieved in response to a concept search query are relevant to the ideas contained in the text of the query regardless of shared terms or language.

Cost savings – Concept versus keyword search

Employees are rarely capable of constructing keyword and Boolean searches that return the data they are looking for immediately. Because of this fact, time is wasted in actually finding what they were looking for. IDC has estimated that using a higher quality enterprise search capability can save up to 53.4% of time spent searching for data. Many have argued conceptual search can save even more time because conceptual search more closely models how humans think and therefor will return more meaningful results quicker.

Alan Greenspan, a past Chairman of the Federal Reserve, once stated “You’re entitled to your own opinions, but not to your own facts”. Return on Investment calculations are only as good as the reliability of the variables used to calculate it. To calculate ROI, the benefit (return) of an investment is divided by the cost of the investment – the result is expressed as a percentage.

Enterprise Search ROI calculations require the following data points:

•           The total cost of the current enterprise search process used

•           The total cost of the new enterprise search process after the investment is in place

•           The total cost of the new enterprise search investment

The actual ROI formula looks like this:

Return on investment is an often asked for but little understood financial measure. Many equate cost savings to ROI but cost savings is only a part of the equation. ROI also includes looking at the cost of the solution that produced the savings. ROI lets you compare returns from various investment opportunities to make the best investment decision for your available dollars.

Organizations run on information. If information is easier to find and use, the organization profits from it.

Information Management Cost Reduction Strategies for Litigation

In these still questionable economic times, most legal departments are still looking for ways to reduce, or at least stop the growth, of their legal budgets. One of the most obvious targets for cost reduction in any legal department is the cost of responding to eDiscovery including the cost of finding all potentially responsive ESI, culling it down and then having in-house or external attorneys review it for relevance and privilege. Per a CGOC survey, the average GC spends approximately $3 million per discovery to gather and prepare information for opposing counsel in litigation.

Most organizations are looking for ways to reduce these growing costs of eDiscovery. The top four cost reduction strategies legal departments are considering are:

  • Bring more evidence analysis and do more ESI processing internally
  • Keep more of the review of ESI in house rather that utilize outside law firms
  • Look at off-shore review
  • Pressure external law firms for lower rates

I don’t believe these strategies address the real problem, the huge and growing amount of ESI.

Several eDiscovery experts have told me that the average eDiscovery matter can include between 2 and 3 GB of potentially responsive ESI per employee. Now, to put that in context, 1 GB of data can contain between 10,000 and 75,000 pages of content. Multiply that by 3 and you are potentially looking at between 30,000 and 225,000 pages of content that should be reviewed for relevancy and privilege per employee. Now consider that litigation and eDiscovery usually includes more than one employee…ranging from two to hundreds.

It seems to me the most straight forward and common sense way to reduce eDiscovery costs is to better manage the information that could be pulled into an eDiscovery matter, proactively.

To illustrate this proactive information management strategy for eDiscovery, we can look at the overused but still appropriate DuPont case study from several years ago.

DuPont re-looked at nine cases. They determined that they had reviewed a total of 75,450,000 pages of content in those nine cases. A total of 11,040,000 turned out to be responsive to the cases. DuPont also looked at the status of these 75 million pages of content to determine their status in their records management process. They found that approximately 50% of those 75 million pages of content were beyond their documented retention period and should have been destroyed and never reviewed for any of the 9 cases. They also calculated they spent $11, 961,000 reviewing this content. In other words, they spent &11.9 million reviewing documents that should not have existed if their records retention schedule and policy had been followed.

An information management program, besides capturing and making ESI available for use, includes the defensible deletion of ESI that has reached the end of its retention period and therefore is valueless to the organization.

Corporate counsel should be the biggest proponents of information governance in their organizations simply due to the fact that it affects their budgets directly.

The ROI of Information Management

Information, data, electronically stored information (ESI), records, documents, hard copy files, email, stuff—no matter what you call it; it’s all intellectual property that your organization pays individuals to produce, interpret, use and export to others. After people, it’s a company’s most valuable asset, and it has many CIOs, GCs and others responsible asking: What’s in that information; who controls it; and where is it stored?

In simplest terms, I believe that businesses exist to generate and use information to produce revenue and profit.  If you’re willing to go along with me and think of information in this way as a commodity, we must also ask: How much does it cost to generate all that information? And, what’s the return on investment (ROI) for all that information?

The vast majority of information in an organization is not managed, not indexed, not backed up and, as you probably know or could guess, is rarely–if ever–accessed. Consider for a minute all the data in your company that is not centrally managed and  not easily available. This data includes backup tapes, share drives, employee hard disks, external disks, USB drives, CDs, DVDs, email attachments  sent outside the organization and hardcopy documents hidden away in filing cabinets.

Here’s the bottom line: If your company can’t find information or  doesn’t know what it contains, it is of little value. In fact, it’s valueless.

Now consider the amount of money the average company spends on an annual basis for the production, use and storage of information. These expenditures span:

  • Employee salaries. Most employees are in one way or another hired to produce, digest and act on information.
  • Employee training and day-to-day help-desk support.
  • Computers for each employee
  • Software
  • Email boxes
  • Share drives, storage
  • Backup systems
  • IT employees for data infrastructure support

In one way or another, companies exist to create and utilize information. So… do you know where all your information is and what’s in it? What’s your organization’s true ROI on the production and consumption of your information in your entire organization? How much higher could it be if you had complete control if it?

As an example, I have approximately 14.5 GB of Word documents, PDFs, PowerPoint files, spreadsheets, and other types of files in different formats that I’ve either created or received from others. Until recently, I had 3.65 GB of emails in my email box both on the Exchange server and mirrored locally on my hard disk. Now that I have a 480 MB mailbox limit imposed on me, 3.45 GB of those emails are now on my local hard disk only.

How much real, valuable information is contained in the collective 18 GB on my laptop? The average number of pages of information contained in 1 GB is conservatively 10,000. So 18 GB of files equals approximately 180,000 pages of information for a single employee that is not easily accessible or searchable by my organization. Now also consider the millions of pages of hardcopy records existing in file cabinets, microfiche and long term storage all around the company.

The main question is this: What could my organization do with quick and intelligent access to all of its employees’ information?

The more efficient your organization is in managing and using information, the higher the revenue and hopefully profit per employee will be.

Organizations need to be able to “walk the fence” between not impeding the free flow of information generation and sharing, and having a way for the organization as a whole to  find and use that information. Intelligent access to all information generated by an organization is key to effective information management.

Organizations spend huge sums of money to generate information…why not get your money’s worth? This future capability is the essence of true information management and much higher ROIs for your organization.