In Process Optimization, Look Beyond the Ax and Stopwatch

Every time I watch an auto race, I’m in awe of the pit crew. During a pit stop, the crew changes all four tires, fills the fuel tank, cleans the windshield, and performs many other tasks -- all in a matter of seconds. It’s the ultimate in process optimization and the key to winning races.

Likewise, process optimization is the key to winning in business. It’s the only way to stay quick on your feet to remain competitive in today’s high-speed business environment. As you focus on optimizing processes, however, it’s essential to look at the big picture.

What do I mean by that? The traditional process optimization approach is what I call the “ax and stopwatch” method. The primary objective is to increase process speed and efficiency. This method involves: 

This method is effective and necessary, but it’s insufficient. You also need to step back and look at your overall goal: What is it you’re trying to accomplish?

Look at the front end as well as the back end

Here's a scenario: An IT team we worked with had been evolving its IT service request process over the years, migrating from a service desk staff answering phones to an online service catalog from which employees submit requests on their own. The goal of the self-service interface was to enable employees to get what they need with minimal help from IT.

With this self-service approach, employees filled out a highly structured online request form. Submitting the form triggered a set of optimized, automated backend processes that routed the requests for approval, kept people informed of request status, and fulfilled the request.

Some employees were able to fill in the required information on their own. Others, however, had to turn to peers or call the service desk for help in filling out the forms. This introduced delays and frustrated employees.

The big picture -- the overall goal -- was to enable employees to request IT services completely on their own. While the axe and stopwatch resulted in back-end processes that delivered maximum speed and efficiency, the goal of self-sufficiency for all employees hadn’t been achieved. To reach that goal, IT needed to expand its optimization efforts to include the front-end request process.

The IT team employed chatbot technology to act as an intermediary for submitting requests. The team optimized the chatbot process for natural interaction, so it doesn’t merely parrot the questions from the form and record the answers. It interacts in humanlike, natural-language conversations. Instead of filling out a sterile form, people converse with the chatbot as it solicits information required to fulfill the request. When employees don’t have a required piece of information, the chatbot helps them to find it.

Although filling out the form may be a faster and more efficient way of entering information for some employees, the chatbot offers an alternate, friendlier channel to make requests for those employees who find the forms intimidating.

The results were gratifying. The chatbot not only reduced the load on the service desk but also boosted employee productivity and reduced frustration, which translates into higher job satisfaction. And, because the back-end processes were already automated, the chatbot leveraged work already done.

Look beyond the original purpose

Looking at the big picture when optimizing processes often results in capabilities that are applicable well beyond their initial purpose. The chatbot example illustrates this point. Although the reason for implementing the chatbot was to provide a more interactive channel for submitting IT service requests, its potential for increasing employee self-sufficiency goes beyond that. Many organizations are already using chatbots to do the following: 

Look at the possibilities

The big takeaway here is this: In process optimization, step back and think about the overall goal. Go ahead and use the axe and stopwatch. At the same time, add a wide-angle lens to your toolkit and explore the big picture.

The example presented earlier describes the use of a chatbot in process optimization. But there are many other technologies today that organizations can apply. Machine learning enables automated processes to become smarter over time, so they deliver better and faster service. Artificial intelligence can help pinpoint process bottlenecks and make recommendations to improve process speed and efficiency.

The possibilities are exciting and endless.

Imran Khan is senior vice president of Customer Success at BMC Software. He leads the Services and Education business, the Customer Support organization, and the Chief Customer Office function. Previously, Imran was SVP of global services and an executive team member at JDA Software. His organization provided consulting and services to the globe’s top supply chains, with services accounting for a third of JDA’s revenue. Prior to JDA, Imran was vice president for worldwide network consulting at Hewlett Packard where he led the industry’s leading networking consulting business.