How to Determine if Integration Can Save You Money

Whether you’re a tech salesperson looking for talking points, or an internal champion trying to drive change and build a case for automation at your company, we hope these ideas and tidbits help you codify a tangible and effective ROI case for automated dataflow between your critical systems.

The Equation

The equation essentially looks like this:

((T*P)+NI) - IP = SPM

T = Time (hours spent on manual data entry per month)
P = Pay (how much you’re paying someone per hour)
NI = New Initiatives (the monthly value of other outputs that person could be driving)
IP = Integration Price (the price tag associated with just the integration component)
SPM = Savings Per Month (a positive SPM means you are saving money)

So, an example would be:

Mary spends 36 hours each month to reconcile expense reports between the field and back office. She earns $40/hr as an assistant controller. The company would much rather have her focus on earning her CPA so she can be on track as a potential CFO candidate (if they were able to hire within, they could theoretically save about $75,000 in headhunter fees). There’s an integration product that costs about $700/m and would automate the manual process that Mary has been doing.

In this example, T = 36 hours per month; P = $40; we’ll skip NI on this example, since the other factors all contribute to the ongoing costs of doing business, rather than the transactional nature of hiring; IP = $700.

((36*$40)) - $700 = $740

Anytime your SPM is greater than zero, then the automation is saving you money. In this example, Mary’s company is spending $740 more per month than they need to.  The integration can accomplish the same amount of work with a lower risk of error and a faster turnaround time on each task. And this is before we include any talk of creating space for Mary to become a CPA and become the future CFO of the company (an initiative that massively outweighs the cost of the integration in this example).

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The Thought Process

Generally speaking, here’s the high-level train of thought (we’ll dive into each topic below):

  1. Identify areas of the business that can be automated and identify the person (people responsible for manually exporting/importing data between systems.
  2. Identify the number of data fields that are impacted between two (or more) systems.
  3. Determine the actions involved with properly moving data between those systems.
  4. Determine the frequency of database updates that happen between those systems.
  5. Quantify the amount of time being spent on the current manual process(es) in steps 3 and 4.
  6. Determine how the company could benefit from having the time in step 5 applied to other areas of the business.
  7. Calculate the savings per month of having people spend time, energy, and brainpower on the manual process(es) in steps 5 and 6 required to move data between systems instead of using their time, energy, and brainpower to focus on preferred areas of the business.
Step 1: Identifying Areas of the Business that can be Automated

Don’t overthink this. Look for people in the organization who “never have enough time” to get everything done. If their task list isn’t overwhelming on paper, then chances are they’re fighting an uphill battle against a bottleneck in the process or they’re spending too much time on tasks that completely kill their ability to be productive.

Questions to ask:

  • Are you able to get everything done each week?
  • What’s demanding most of your time?
  • Do you feel like you’re wasting time on anything?
  • Can I shadow you while you do those “time-wasting" tasks?

This step should be repeated as often is necessary to ensure the business is leveraging people’s time effectively.

Steps 2 & 3: Identifying the Data Fields that are Impacted Between Two or More Systems

For the most part, this can be tackled by taking a look at the spreadsheet that’s exported from one system and then imported into another. Ask the person responsible for export/import process to show what steps they do to make sure the file is ready for import. Take note of the headers in each column; they represent the fields in each system. Take note of the field types (are they open text? pick list? numerical? calculation? multi-check box?).

Questions to ask:

  • What do you do to ensure the data is accurate and ready for import?
  • Do you ever have to get clarity from your colleagues about the information they’ve input? If so, how do you handle that and how much time does that take?
  • Are there any fields that you wish were pick list instead of open text?
  • Do you have to process any calculations before import?
  • Do you have to manipulate the data before import?
  • Do you have to copy/paste anything to get the file ready for import?
  • Do you have to do any file type changes (.txt to .csv, for example)?

This step should be repeated as often is necessary to ensure the business is leveraging people’s time effectively.

Step 4: Determining the Frequency of Database Updates that are Triggered between These Systems

The core focus here is to understand what actions in the overall workflow between the systems would cause the other system to need to make changes to its database.

Questions to ask:

  • Which fields should be kept in sync with the other system at all times?
  • Which system should be considered the dominant source of truth for a given field?
  • To ensure the systems are kept apprised of changes on either side, how frequently does the export/import process need to happen?
    • Note: the answer here can vary depending on the data field. Some data will need an instant sync based on a trigger. Other fields might only be updated on a weekly or monthly basis.

Determining the frequency will help you identify the number of interruptions that the manual process creates for people. This will be powerful when determining the ROI. Even further, it will give you the opportunity to identify process bottlenecks and avoidable breakpoints for productive work patterns in your organization.

Step 5: Quantify the Amount of Human Time this Process Requires

During your discussions with key stakeholders, be sure to take note of the estimated amount of time they need to complete each task. This might require some effort to triangulate, but having an accurate accounting of how much time the manual effort associated with data export, data manipulation, data validation, and data import actually requires is essential to understanding the true costs of this manual process.

Step 6: Determine Other Uses for That Time

If you think automation is a way to figure out how you can reduce headcount, then you’re approaching this exercise with a limited mindset. Automation isn’t about reducing headcount or keeping costs down, it’s about achieving maximum output from your most valuable asset – your people. For all the praise that modern technology gets, the human brain is still the creative powerhouse that holds the key to corporate success. Automation is about leveraging technology for the mundane, error prone, medial tasks that can kill employee morale. Free your people. Think bigger about how they can become strategic critical thinkers for some of your company’s challenges.

Questions to ask:

  • If we could eliminate this manual process from your regular routine, how would you like to grow here? What other responsibilities would you be interested in taking on?
  • What other challenges have you identified in your role that you simply can’t get to because you’re too busy?
  • What opportunities do you think we’re leaving on the table? If we created more time for you, would you be interested in pursuing those opportunities?
Step 7: Determine if Your Company Can Afford Not to Integrate

When you put the price tag of an integration up against the current costs of the manual effort, more often than not, you’ll find that you’re already spending more money than you need to. And that equation only becomes all the more exacerbated when you consider the opportunity costs of new initiatives that go untouched due to the fact that your people are “too busy.”

What’s at the Center of your Tech Stack?

Good tech buyers know that they should consider the integration capabilities of a given tool when making a purchase decision. Great tech buyers know that when they design their tech stack, they should start by putting data at the center of attention. It’s commonplace in construction to put the ERP at the center of the tech stack, and while that might have been appropriate at the time, it’s now time to consider the ERP as a tool in the stack. By putting data at the center of attention, the tech stack becomes much more nimble, much more adoptable, and much more informative.

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