February 8, 2022

Why You Need to Invest in Analytics Before You Invest in Automation

Before you work on automation for your operations team, make sure you have the proper analytics to know what to automate and how to measure the impact.

In the last two years, we have started to see the dramatic rise of RPA (Robotic Process Automation) in the enterprise. Companies like UIpath, Blue Prism, Work Fusion, and Tonkean are enabling companies to build ‘bots’ to perform routine tasks and focus team members on the most important human work.

RPA is clearly the practical future of automation in the workplace. The leverage that companies are getting out of being able to ‘script’ the rote parts of their human work, and focus their operations workers on the most impactful work is demonstrable and meaningful.

The challenge in implementing RPA is knowing what to automate, how to automate it, and then understanding the ROI of your investment. 

Measure Before You Start Automating

You can’t start down the path of using RPA until you know what to automate. And you can’t really know what to automate until you understand in detail what your teams are spending time and effort doing.

Until you have that insight you cannot properly decide where to invest in automation, and then understand the impact of the automation you build.

As of today, almost no companies actually have this knowledge - because human knowledge work is notoriously hard to measure. That leaves really only two paths:

Option 1: Implement RPA without insight into your existing workforce

Many companies are doing just this - skipping analytics and jumping right into RPA. This is not advisable. It makes it impossible to know whether or not the effort you are putting into automation is being well spent, and impossible to know after the fact if your investment truly paid off.

There is enough excitement about automation that many organizations go down this path in the short term, but without the data to support that these investments being made in automation are the right ones, this is not a great long-term strategy.

Option 2: Do Time and Motion Studies with Consultants

Major consulting firms have been doing time-and-motion studies for decades for large enterprises. For six or seven figures, a great consulting firm will send people to watch and document the operations work of your company and give advice on where automation should fit.

This is better than doing no measurement at all, but this is an antiquated approach to solving the problem.

At best, this approach gives you a small sample of the work being done as consultants can only study a subset of your population. Because it is largely manual work, it also doesn’t scale well for follow-ups, and often misses important nuances.

Measurement that Enables Automation

The product my team and I are building now, Fin, provides the missing data needed to pinpoint exactly where the opportunities for automation exist within operations organizations. Imagine having access to a data stream of every click, keystroke, page visit, and more across your whole team, and the ability to playback a video recording of any moment in the day. This type of measurement goes beyond the scope of any time-and-motion study and the traditional ‘outcome statistics’ that most teams are using today (things like CSAT, NPS, Handle Time, etc.), and gives you a precedented look into how work is being done.

By analyzing the process data associated with your team’s operations work, you’ll be able to understand where the biggest opportunities for automation lie, how to deploy that automation into a given workflow, and precisely measure the impact of your automation efforts.

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