A well-known UK food retailer was experiencing two major issues with their refrigeration maintenance program.
Firstly, they did not have a complete picture of work orders being raised across their estate, as their data was too disjointed to provide useful analysis. Secondly, engineering costs were rising without any understanding of why..
The customer has four servicing contractors operating on the estate, all reporting in different ways. This made it difficult for the teams to understand if they were receiving value for money from the contracts they had in place.
The client wanted to get a clear, estate-wide understanding of total work orders raised per site, reduce the number of repeat orders and effectively track the performance of the company’s four contractors against their contractual SLAs. The data shown within this case study compares numbers from March 2019 (shortly after LoweConex was deployed) and the same month in 2020.
LoweConex was deployed to monitor live running and alarm telemetry for all refrigeration assets estate wide. API was generated, along with rule-based logic, to understand alarm conditions and automatically raise work orders directly with relevant contractors, and only when necessary.
LoweConex then uses data modelling and graphical outputs to give the teams a clear view of the current and historical data around work orders, report work orders and compliance to SLAs.
The below image shows live work order volumes tracked & graphed. All data is displayed in real-time, with a summary dashboard which groups alarms by equipment type and more crucially the repeat work orders and SLA percentages.
The LoweConex work order reporting section provides multiple dashboard views allowing the teams to cycle through different combinations of data. The below image shows the total work orders raised per site and an average per contractor, for March 2019.
The next dashboard gives a percentage of repeat work orders that each of the four contractors are producing estate wide. The assumption being, less repeat work orders means the contractor provides more conclusive fixes at the time of visit and therefore is more cost effective. In March 2019, contractor 4 was outperforming all others with regards this metric.
The final set of metrics is a customisable aspect of LoweConex. It feeds in the live data from the work order system and the 3rd party engineering software to automatically produce a percentage of the total work orders that are ‘out of SLA compliance’.
The customer can then use this to activate SLA penalty clauses or as information when decision-making on contract renewals. For example, in 2019, contractor 1 only met their SLA targets 30% of the time, compared to 60% with contractor 4.
After 12 months of targeting improvements based on the data, using rule-based logic and AI-driven fixes applied directly to the refrigeration, the customer has seen a dramatic improvement across all three of the metrics. Average work orders per contractor per site fell across the board in March 2020, as shown below
After 12 months the percentage of repeat orders per contract has reduced by an average of 10% in all but one (contractor 4). The most dramatic fall has been contractor 1, who across the board was the worst performing prior to LoweConex being deployed.
The final set of results shows the overall ‘out of compliance SLA’ percentages.
There have been reductions in 3 out of the 4 contractors, with the most dramatic again coming from contractor 1 who has made huge strides in the quality of service being provided to the customer.
LoweConex has driven costs down, improved contractor transparency and performance, leading to increased up-time and a reduction in maintenance costs.
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