Written by Bill Finger, Managing Director, Kineticos

Four years ago, I got into consulting after a long career on the service provider side of diagnostics. To me, consulting is exciting; primarily because I’m provided with an opportunity to make an impact on so many companies by helping them with a variety of challenges. Most often, my team is focused on assisting companies with commercially focused priorities but more than a handful of times over the last 4 years, we’ve been asked to help companies address operational issues that they are experiencing. I wanted to share with you a few things I’ve learned through the course of helping life science companies achieve operational excellence.

Starting with the basics, Operational Excellence is a rather broad term used across all industries. It describes the processes, tools and systems used to run a business effectively. What many forget is that the goal of Operational Excellence is to continuously improve operational, financial and quality metrics. Easy enough, right? It’s not as easy as it sounds.

Understanding strategic goals is critical in setting company metrics. The goal may be to have excellent customer service, increased revenue growth, improved sales or greater EBIDTA. Once everyone understands what is most important to the company, it’s time to measure it. Below are a few types of metrics to consider as a part of an overall Operational Excellence program.

Output metrics are focused on the goals of the company. These metrics are more common and include financial metrics like revenue, profit and EBIDTA. Other types of metrics focus on customer service – Net Promoter Score (NPS), response time and customer complaints to name a few. Sales metrics include net sales, net new business and lost proposals. These are good indicators of the state of a company, but do not give much insight into a company’s operational strengths and weaknesses.

Input (process) metrics measure how tasks or workflows are being performed. They’re often not treated with the same level of attention as output metrics but are at the core of any operational excellence initiative.   For example, on time delivery or turn around time are commonly collected metrics. What if we (or more importantly, our customers) are not satisfied with the on time delivery provided? When this happens, I try to dig deeper into the process and look at metrics that measure each step of the process. Look at the time it takes to perform each step and variations across employees. Include error rates by technology, process flow and employee. I’ve learned that going through this process will innately uncover issues around training, redundancies of process, and even workload issues.

I’ve also learned that it’s important to keep an eye on how one process may impact another. For example, labs can often be so focused on getting their runs complete in order to meet their customer’s timeline that the staff are forced to rush through their processes, which inevitably leads to errors. Errors made in a lab will increase the time it takes for quality assurance (the subsequent process) to complete their tasks. Even the smallest of errors in a sub-process can make a significant impact on the efficiency of an overall process.

Evaluating metrics, especially input metrics, can be a daunting task but leveraging them to identify and fill operational gaps can dramatically impact the bottom line. Keep in mind that if it can be measured, it can be improved.

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Bill Finger, Managing Director of Kineticos’ Diagnostics Practice, brings 20 years of diagnostics and laboratory experience to the team.  His team is focused on helping diagnostic companies maximize their commercial potential at the corporate and product levels while ensuring companies operate in an efficient manner.

Contact Bill