Illustrations : DrAfter123 data interpreted by its proprietary software Predix , allows operators improved efficiencies and enables preventative maintenance before units malfunction , mitigating both uninsured and insured downtime .
Assistance for underwriters ? Could underwriters follow telematics car insurers ’ lead and harness industrial operational data to specifically price a product for companies which provide access to this data ?
Faster settlement of claims ? Typically files provided on a large energy claim can run to hundreds of megabytes , if not gigabytes . This can include refinery Linear Programming , petrochemical production data or hourly power plant data containing detailed statistics such as : ambient temperature ; availability ; generation ; flow rate ; heat rate ; fuel usage ; or utilities usage . Whilst arguably not in the realms of big data , it is sufficiently large to require a forensic accountant to mine and distil down for Insurers consumption .
Enterprise Resource Planning ( ERP ) systems allow extraction of specifically tailored datasets of Production , Sales and Inventory to assess BI losses , reducing the time spent by the Insured manually preparing reports , which would require verification back to source records anyway .
Time can be better spent on analysis issues relevant to the quantum of loss , improving response time for updates , interim payments and settlement figures .
More accurate loss measurements ? Increasing volumes and granularity of data allows quantification of losses which would have been unsupportable historically , for example :
• Analysis of heat rates and fuel burn to identify turbine efficiency losses following non-catastrophic damage
• Identifying loss of capacity on a specific turbine
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