CMMS by the Numbers: Frito-Lay's KPI Journey

Disciplined Process Execution Is Key to Data Integrity--and Savings

By Walt Boyes

Invensys Microsite

"Too much data…not enough data...the data isn't relevant…or the crowning, 'Does anybody even look at this report?'" 

Ed Michel, reliability manager and Frito-Lay corporate subject matter expert on CMMS (computerized maintenance management systems), began his presentation at this week's meeting for users of Invensys Operations Management's Avantis and Wonderware software reviewing all the reasons that many CMMS implementations fail to reveal opportunities for efficiency gains.

It is easy, he noted, to think that more data is better. But the integrity of the data is really the controlling factor. "Data integrity is foundational for analysis," he said. "At first we just tried to collect as much data as we could. We realized that regardless of the CMMS, there is a human input and process execution that must occur to get meaningful data." Otherwise, what may look like good data really is not.

At Frito-Lay, they started out by taking the "more is better" approach, developing scorecards down to transactional activity by date, by shift, by time and by occurrence. "We transitioned to 'Leading Indicators' and instead of giving maintenance people a scorecard on which they expected to be graded, we gave them a dashboard so they could be in control," Michel said.

Because it is a dashboard, it can grow and change, he noted. "Are we getting the most out of our CMMS based on the data we collect? No, of course not," he said. "But it is a process. As we continue to drive downtime to 4.0%, we will need to rely more on our information systems to identify trends. How do we gauge our efficiency and not just downtime?"

Michel showed a typical dashboard, and how it can be used for in-depth analysis. For example, there was an indicator labeled "% Generic." This is the data descriptor people enter into work orders when they don't know what the part is, or don't want to go look it up, according to Michel. This entry makes the data useless, so keeping a tally on the number of times it is used allows Michel to make a judgment on how effectively someone is using the CMMS. Each of the metrics in the dashboard is rated, from Traditional to Standard to Advanced and finally to World Class. "You can see on the dashboard how your results stack up."

Taming Excess Inventory

Over the years, many sites' inventory levels have grown, Michel continued. New capital means new spares, and replenishment points have not been optimized to take account changing needs. Obsolete inventory at one site may not be obsolete at another. "And as our reliability performance improved, the need for inventory has gone down," Michel said.

To translate reduced inventory requirements into savings, Frito-Lay developed an inventory analysis tool that takes into consideration usage, lead-time, and replenishment method to suggest new set points for replenishment. The company also was able to provide electronic visibility into surplus inventory at other sites, preferentially transferring existing surplus stock in favor of requisitioning new parts. This methodology totaled some $3 million in annual savings, a number they were able to increase by $1.1 million simply by facilitating "mass moves" of surplus inventory (rather than individual transfers) to sites where those particular SKUs were still needed.

The next step for Frito-Lay in its CMMS journey was to deploy the Avantis Decision Support System, Avantis.DSS, for end-user analysis. It has allowed Frito-Lay to stop exporting data to Excel spreadsheets and Crystal Reports and allows end users to set up their own web-based key performance indicator (KPI) dashboards without signing into Avantis itself. A large selection of standard maintenance, inventory and purchasing KPIs is built over a separate information data warehouse to minimize performance impact on the Avantis database itself.

But the effective use of Avantis.DSS relates first to the integrity of the CMMS data, Michel stressed. "Above all, data integrity begins and ends with work processes."