This is the third in my series of four postings on what I consider the four most critical elements to starting a Lean Six Sigma (LSS) project (see part one and two). Revisiting the four elements, they include:
- Writing a “great” problem statement.
- Identifying a primary metric that best measures the problem.
- Establishing a business case for why a LSS team should be used to fix the problem.
- Defining what “success” means.
The third element is perhaps one of the most challenging in starting a LSS project, especially when working in a transactional environment. I often find the belts and champions I mentor have little to no problem quantifying the financial impact of a problem related to defective product so I’m not going to spend any time in this posting discussing these types of projects where all you need to do is look at the historical pile of scrap and rework and put dollars to it.
Where the challenge comes is when the opportunity to improve is related to work being done by people, but before we get to counting the money we need to start with revisiting the problem statement.
Starting with the problem will help zero in on where the money may reside. Below is an example problem statement:
In the new patient registration process when transferring patient insurance information to the electronic billing system 30% of patient records have errors not meeting our goal of 99% accuracy.
This inaccurate insurance information leads to rejected claims that create both delays in payments, and in some cases no payment for services, in addition to incorrectly billing patients directly who then become less likely to return for future services.
I routinely work with belts and champions who find this process challenging because they start with the belief they have to begin with a dollar amount instead of working forward from the problem statement to arrive at a dollar amount.
The first step in the process I use to determine the financial impact of a LSS project (this is often referred to as Cost of Poor Quality or COPQ) is to ask the following questions with the answers being put into words and not numbers.
- What is the negative impact if the problem is not solved?
- What is the positive impact if the problem is solved?
Facilitating this process can be done a number of ways, but I prefer simple brainstorming with post-its and / or a whiteboard. Using our problem statement example, the answers might look something like this:
Negative: rejected claims, delays in payment, no payment, incorrect billings, lost patient revenue
Positive: on-time payments, increased revenue
With the answers to these questions I will narrow down the list to the top 3 and begin the next step of building a formula for estimating the business impact. In this example the most impactful measures are rejected claims, no payment, and incorrect billings.
The challenge now becomes converting these high impact areas into a formula we can begin to put numbers to. I like to start with a question such as, “what happens when a claim is rejected?” From this answer we will begin to see people and process activity that can be converted into dollars.
For example, what happens when a claim is rejected is that the office claims manager has to modify the claim and resubmit to the insurance company for payment. These are actions that can easily be quantified.
For example, each modification takes an average of 30 minutes, and resubmitting another 15 minutes for a total of 45 minutes per rejected claim. Using an hourly rate for the office manager of $50 / hour, each rejected claim can be estimated to cost ~$37 (.75 hours x $50 / hour).
Breaking this down even further, the Cost of Poor Quality could be defined as:
COPQ = # of rejected claims x $37
This is just one of the three elements we identified as the most impactful, which would lead to the same process being completed for no payment and incorrect billings. The following is an example of all three combined for a total COPQ.
COPQ 1 = # of rejected claims x $37
COPQ 2 = Total $ lost because of no payment
COPQ 3 = # of incorrect billings x $50 (an incorrect billing takes 1 hour to fix)
Total COPQ = COPQ 1 + 2 + 3
The challenge in this process is not to get too hung up in overworking the numbers for 100% accuracy. We’re not looking for five decimal accuracy here. What we are after is to simply get a close enough estimate to help us answer the most important question-does the project merit the time and effort it will take to use the LSS process to solve the problem?
The answer to this question typically lies within the hands of the project champion. Every organization is different, but the process should be similar in that there are lots of opportunities for improvement within a process, and estimating your COPQ is just one more data point to help determine where the opportunity ranks against all other opportunities.
I also urge the belts and champions I work with to get finance involved in this process early in the Define phase. There’s no worse feeling in getting ready to claim victory in the Control phase only to find out the financial assumptions made early in the process were flawed.
Sharing your assumptions and COPQ formula with your finance group will go a long way in ensuring when you do succeed the savings will be valid and your team will end the project on a high that leads to looking for the next opportunity.