Fire the Process and Increase Efficiency!

Are you facing the pressures of improving efficiency with minimal resources and increasing customer demands?

Do you know what is causing your current cost or efficiency issues? Is it the amount of overhead? Is it performance flaws of your employees? These are all areas that should be explored and not discounted. But, one area that is frequently overlooked is the numerous amounts of process issues impeding success. These process issues can actually increase cost, increase delay time to customers, and decrease efficiency.

Have you thought about the impact poor processes have on employee morale and retaining top talent? I will show a solution to rapidly quantify some key process issues that will help in prioritizing improvement efforts.

Employees are commonly measured by their ability to execute. Unfortunately, we do not always measure the process in the same manner. Negative impacts of a process can be masked by symptoms appearing to be employee performance related.

What if I told you there is a simple way to visually see what is happening throughout each day and in enough detail to be able to take rapid action to increase efficiency? What if I also told you that you could start this analysis today and be done in a week or less?

There is a tool called Overall Equipment Efficiency (OEE) that was originally developed for the manufacturing environment. OEE is very valuable, but it has detailed content that may not apply to your current business needs. I’ve adapted this tool and created a simple method to help companies in non-manufacturing environments effectively measure efficiency.

Let’s take a look at an example. John is an employee who is considered top talent. He processes tickets that are opened internally by a separate department and then sent to John for processing. These tickets are time sensitive and address critical customer needs. For this example, we will assume the work day is 8 hours including lunch and breaks.

Current Situation:

• On average, John can produce 40 tickets a day.
• Recent forecasts of ticket volume show that there is an urgent need for John to process 70 tickets a day.

Possible Solutions:

• Find a way to make John more efficient in how he processes tickets. A proposal was created to add technology that would allow John to process tickets faster. It would cost $10,000 and take two months to implement.
• Have John work overtime.
• Hire additional resources.

The company decided they cannot hire additional resources at this time and chose to go with the proposal to add technology. They believe if they can make John more efficient with the technology, then he will be able to process 70 tickets a day and eliminate the need for hiring additional resources or adding overtime costs. Seems to make sense, right?

But, what if I told you that John’s current efficiency of 40 tickets a day was not limited by his ability to process tickets faster, but rather it was due to something else? I see many companies focus a large amount of effort and dollars on how to make an individual do something faster while missing the processes that are impacting efficiency. Don’t get me wrong, improving technology to help John process tickets faster is not a bad solution. But, is it the right solution for the current situation? And, will it deliver rapid sustainable results?

By measuring what John is dealing with during his 8 hours a day, we can uncover something called “hidden losses.” These types of losses are missed because some issues occur so often and are short in duration that people become desensitized and just deal with them and move on. However, when summing up all the hidden losses, we end up with a potentially significant amount of impact. We often notice issues that lead to a significant time loss, such as a major software crash. But we often miss the little things, such as repeated minor software delays or repeatedly missing ticket information, that when added together becomes very significant.

For this example, I created the following buckets:

• Set Up/Shut Down: The time spent setting up and logging into computer software for the day, along with time spent closing applications and shutting down before leaving for the day.
• Planned Down: The time spent for breaks, lunches, and meetings.
• Major Interruption: Interruptions preventing work on processing tickets due to a major issue, such as a software crash, that are more than 30 minutes for each incident.
• Minor Interruption: These are the “hidden losses.” For example, this is an interruption in processing tickets that’s less than 30 minutes per incident, such as a ticket with missing data, a quick interruption from someone needing information, or a document waiting on a signature.
• Working: This is the time spent working on processing a ticket without any type of interruption. In a sense, it’s when John is processing a correct ticket.

Results from the analysis of one day as well as for one week are shown below. During John’s 8-hour day, he spent only 1.17 hours processing tickets. Of the 40 hours for the week, only 10.58 hours were spent on processing tickets.

Surprised? This is not an exaggeration. It‘s very common to see such a small amount of actual working time. Trust me, it will be shocking at first. But, the ability to rapidly fix the issues after the analysis will make for a great success story.

Now, let’s go back to the proposal that was created. Reviewing the chart above, would we gain very much by spending $10,000 and waiting two months to increase John’s ability to produce tickets faster during his 1.17 hours? Absolutely not. Instead, we should focus on all the other buckets that are impacting John, such as meetings, major interruptions, and minor interruptions.

Analyzing the data collected in the minor interruptions bucket yielded the top 4 hidden losses:

• Ticket missing information: 30 occurrences accounting for 20% of this bucket.
• Waiting for signature approval: 15 occurrences accounting for 30% of this bucket.
• System re-boot: 4 occurrences accounting for 10% of this bucket.
• Peers stopping by to discuss a project: 3 occurrences accounting for 10% of this bucket.

As a result of the analysis, the following rapid actions were taken to address the top two issues:

• Ticket missing information: Fix was implemented to departments’ processes to ensure data is not missing.
• Waiting for signature approval: The existing process required 5 signatures, but it was quickly determined that 3 of the signatures were not required. As a result, 3 of the signatures were eliminated and the process for waiting for signatures was improved.

Additional benefits:

• Planned down bucket analysis: This resulted in a reduction in the quantity of meetings John was attending.
• Cost avoidance: The cost of implementing technology to make John process tickets faster was avoided. In addition, the cost of having John work overtime was avoided.
• Employee morale: As a result of these improvements, John felt motivated and valued by his employer.

So, the next time you’re faced with the pressures of improving efficiency with minimal resources and increasing customer demands, remember to look beyond the person and think about “Firing the Process and Increasing Efficiency!”

Please feel free to contact me or visit my link below for more information.

Process Evolution, LLC