Performance Metrics (last 12 month avg.) | MFT | MFT | MFT Advantage |
Errors / exceptions / problems, as a percentage of the total annual volume of transfers | 3.3% | 4.5% | 26% |
Time to correct an identified error / exception / problem | 81 | 387 minutes | 4.8-times |
The comparison is easy enough to understand: MFT users experienced 26% fewer errors, exceptions, and problems as a percentage of the total annual volume of transfers, and they were 4.8-times faster to get going again when an error, exception, or problem did occur.
This is nice information to have for marketing purposes, but what does it really mean for the business?
A couple of quick, back-of-the-envelope calculations based on these findings shed some interesting light on this question:
- Let’s base our analysis on an annual volume of 1,000 file transfers. This makes it easy for you to personalize for your own particular environment – for example, if your annual volume is 10,000 transfers, you can simply multiple these results by 10.
- Let’s assume that the average percentage of errors, exceptions, and problems is as shown above
- Likewise, let’s assume that the average time to correct errors, exceptions, and problems is as shown above
- A simple computation leads us to the following:
- 1,000 transfers * 3.3% * 81 minutes = 2,711 minutes lost per year for MFT users
- 1,000 transfers * 4.5% * 387 minutes = 17,331 minutes lost per year for MFT non-users
Now, let’s think about the cost of that lost time. In a person-to-person scenario, there are at least two people affected – and arguably three:
• The sender of the file loses at least some of their productivity
• The receiver of the file loses at least some of their productivity
• In addition, the issue may require the involvement of an additional person to help respond, remediate, and recover – and this responder loses all of their productivity
For the sake of this back-of-the-envelope calculation, let’s further assume:
- The fully-loaded cost per person is $50 per hour
- Both sender and receiver lose one-third of their respective productivity for the time the issue remains uncorrected (e.g., they can still do other work)
- The responder, however, loses 100% of their productivity for the time the issue remains uncorrected
- A simple calculation leads us to the following:
- 2,711 minutes * 1 hour / 60 minutes * $50 / hour * (1/3 + 1/3 + 1) = $3,750 lost per year for MFT users
- 17,331 minutes * 1 hour / 60 minutes * $50 / hour * (1/3 + 1/3 + 1) = $23,975 lost per year for MFT non-users
This is a 6.4-times advantage for MFT users, for the cost of lost productivity alone!
If this wasn’t already a sufficient business case for a MFT solution, we could also estimate additional costs related to errors, exceptions, and problems with file transfers, such as:
- Opportunity costs
- Loss of current revenue
- Loss of future revenue
- Inability to carry out the organization’s mission
- Costs associated with the loss or exposure of sensitive data
- Costs associated with non-compliance
I won’t attempt to quantify these costs here, but it seems clear enough that if we did then the gap between MFT users and MFT non-users would grow even wider – e.g., Aberdeen’s research confirmed that compared to MFT non-users, MFT users had fewer security incidents (e.g., data loss or exposure), fewer non-compliance incidents (e.g., audit deficiencies), fewer errors and exceptions, and fewer calls and complaints. As if we needed any more convincing.
Remember, these calculations were done on a volume of 1,000 file transfers per year – you can easily scale these up to reflect your own environment. It’s pretty easy to see that it doesn’t take very much volume to justify the cost of implementing and supporting an MFT solution. (In fact you might even save in operational costs, from the benefits of having a more uniform and efficient file transfer “platform”.)
Another thing we might want to do with Aberdeen’s research findings is to show how MFT users have actually reduced their risk compared to that of MFT non-users – using the proper definition of risk, which has to do with the probability of an error, exception, or problem and the magnitude of the corresponding business impact. The results of that more sophisticated analysis would not be a single, static number (such as the ones we derived above), but a more realistic range of values that would support making business decisions about file transfer based on the organization’s appetite for risk.
In my next post I will dig deeper into the business case for MFT by using a proven, widely-used approach to risk modeling called Monte Carlo simulation.