Part 2 - The Link between Information Management and Data Value

In my last blog, I discussed the connection between information management and data value. I laid out a math exercise showing how a lack of information management can dramatically affect productivity across the organization by calculating the actual cost of employees not being able to find information when the need it. This in turn causes employees to waste time looking for it, and when not found, being forced to recreate it. By estimating the number of hours of lost productivity as well as the fully loaded cost of the average employee, we are able to determine the total cost of lost productivity.

Taking this theme further, we can use the estimate of lost productivity hours and calculate total lost revenue – the revenue the company could have captured if enterprise-wide information management was more efficient.

So let’s start with the lost productivity numbers from the previous blog. For this fictional company we estimated an average fully loaded employee hourly cost of $43. The total hours of lost productivity was estimated to be 65 hours per employee per year of lost productivity due to inefficient (or zero) information management processes. These two number gave us a total annual cost of lost productivity per employee of $2,795.

What could have been done with that lost productivity?

Most organizations are measured on total revenue and profit. Looking back at the average lost employee’s productivity of 65 hours (over 1.5 weeks) what additional revenue could each employee generate if that lost productivity was instead used to generate additional revenue?

Most companies and financial analysts will calculate the average revenue per employee (RPE) to compare company’s performance with others in the same industry. To calculate the average revenue per employee, you simply divide total sales (revenue) by the total number of employees. For example, Phillips 66 has an RPE of $5.7 million, McKesson an RPE of $2.8 million, and Apple an RPE of $1.9 million.

Continuing with our 1000 employee example, let’s assume an RPE of $250,000. To calculate the average hourly RPE, simply divide $250,000 by the total numbers of hours worked per year (most use 2080 hours per year). So $250,000 / 2080 = an hourly RPE of $120.

Calculating total lost revenue

 For our example we calculated an RPE of $120 per hour. To calculate the lost revenue or opportunity cost of ineffective information management, multiply the already calculated lost productivity hours; 65 per employee per year by the RPE of $120. This produces a total lost revenue per employee of $7,800, or $7.8 million for this entire fictional company of 1000 employees. Again, this represents the dollar amount that could have been generated if lost productivity was zero; an unrealistic expectation. So to make it more believable, you can multiply the total lost revenue by a discount factor such as 60%, 70%, or 80% - whatever you CFO is comfortable with. Using a discount factor of 60% we calculate a still very large opportunity cost of $3.12 million, a number that if recovered, could pay for a top notch information management system with a sizable sum left over.

To some, this lost revenue number is unbelievable and to others not a big deal. In fact, several years ago I had a CFO of a medium sized company remark that the opportunity cost or lost revenue number I had calculated was a “soft cost” and therefore he did not think it was important. Over time the same CFO admitted that recovered productivity hours should have a positive measurable effect on total revenue.

Getting control of your corporate data

Affecting your company’s lost productivity and revenue due to questionable information management practices is relatively straight forward and can be paid for by the money you save (a positive ROI). The main point with corporate information is that almost all of it can be important and useful to someone.

Most companies simply ignore the content that is not considered a record – usually considered to be 5% of total content in a company. This leaves the 95% of non-records to be ignored by the company and managed by individual employees. The problem with this strategy is it flies in the face of decades of experience.  Employees don’t have time to read, internalize, and act on the 13 to 15 MB of data they come into contact with daily so they leave it where it lies (the email system) or drag it into several  catch-all folders making search more difficult. So the first step is for companies to accept that all corporate information needs to be managed in some manner.

The next step is to understand where your corporate information is coming from, where it’s stored, and who has control of it. The most obvious sources are the email system, file system, various SharePoint instances, and individual employee computers. The key is to capture it, centralize it, make it searchable, and actively manage it.

I have seen companies capture this non-record data by centralizing the employee storage function by only allowing an employee’s computer to save files to a target folder such as the “My Documents” folder. The company then automatically syncs this folder to a central employee file system folder so the company can have access to it when needed while the employee still has a local copy they can use when traveling. This solution is a good first step however, the data is still spread out among several silos with little indexing so is relatively hard to search.

And finally, at 13 MB per day, the annual amount of stored data per employee will be in the 27 GB range. Multiply that by the number of employees (1000) and you end the first year with 27 TB or a whopping 81 TB at the end of the third year.  

There are three obvious issues with large un-managed storage repositories;

• They are usually un-indexed so finding specific content when needed is time consuming and can be “hit and miss” depending on the search technology used.
• They do not usually include data management capabilities so the information tends to pile up indefinitely
• And enterprise-class storage tends to be expensive when considering the fully loaded cost per GB.

Recovering lost productivity and revenue

A solution many companies are adopting is extending their file system storage up to a cloud-managed platform to take advantage of the much lower cost of cloud storage, up to a 90% cost reduction. The other obvious benefit is they can begin actively managing this huge amount of content with company-defined retention/disposition policies. With this strategy, companies define what content is kept locally (on the local share drive), for example by owner, date last accessed, age, etc., with the vast majority of data being pushed to the cloud for active management. This solution ensures the data is centralized, indexed, actively managed, and kept in the most cost efficient storage available.

Archive2Azure Cloud-Based File Share Extension

Wouldn’t it be great if you could centralize and manage all data instead of being forced to keep expensive enterprise file shares on premise and relying on employees to actually manage their data.

Instead, capture and manage all data into a centralized repository such as file shares, and extend them to the Microsoft Cloud (in Azure) and realize the cost savings from reducing or eliminating new enterprise storage purchases.

Archive2Azure now provides the capability to extend and manage file shares in Microsoft Azure, providing additional capability such as access control, retention disposition, search, encryption, audit/reporting, and a much lower cost per GB.