Analytics Services
Operations Analytics
“What gets measured gets managed.”
– William Thomson (Lord Kelvin)
Operational analytics is a specific type of business analytics. Depending on different business natures, operational analytics may cover sales, retailing, marketing, manufacturing, financing, and many more–as it is a broad category. During the past few years, the technology used in operational analytics has evolved from manual to automated, from reactive to proactive. One thing is for sure, it is applied to increase business transparency through data and improve the status quo.
Many industries have witnessed and enjoyed the benefits brought by operation analytics. Manufacturers can utilize predictive analytical tools to smooth production processes by proactively fixing equipment issues and minimizing supply chain risks. Retailers can visualize customer purchasing patterns and modify product price and inventories based on the feedback from real-time data. Restaurant service industries also adopt monitoring systems that help to refine menus depending on traffics. Even when we walk into casinos, the selection of games is optimized by big data to give us a positive experience!
Mission Critical indicators you should be tracking, but not limited to: [i]
Retail
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Sale per square foot
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Average customer spend
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Stock turnover rate
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Sell through rate;
Manufacturing
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Capacity utilization rate
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Cycle time
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Percentage reduction in downtime
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Maintenance cost per unit
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Unused capacity expenditures
Services
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Average revenue per guest
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Complaints per head
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Complaints per order
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Labor cost per guest
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Profit per table
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Occupancy rate
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Seating efficiency
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Average training cost per employee.
More advanced methods:
Apart from these common KPIs, many new operation metrics have begun being used by startups. Split testing or A/B testing numbers[ii], a conversion rate optimization metric, compares two virtually-identical variations of the same ad or web page, with only one difference, say, the same fashion model wearing the same dress but in different poses. Website visitors are split into two groups with each seeing only one of the two versions so that marketers can measure what effect each page has on their online behaviours and on conversions. As today so many companies rely heavily on internet marketing, cutting out poorly-performing ads would be an effective way to save marketing budget for other operation facets. Another interesting KPI example may be runway, calculated using cash reserves divided by burn rate.
However, it keeps companies aware of a scary but vital fact: how long until they go broke!
Although operation analytics may cover multiple fields, an analysis can always be broken down into three sections–diagnostics, implementation and sustainability–with a gap analysis comparing actual performance data with company goals throughout the whole process. Specific deliverables may include, but not limited to, dashboards showing real-time KPI values, visualization tools summarizing the results of the gap analysis, automation tools and reports elaborating problems and solutions.
Any company of any size in any industry can benefit from operation analytics, but perhaps it is the healthcare industry that has the most to gain. At a Texas hospital[iii], for instance, the readmission rate of cardiac patients has decreased from 26.2% to 21.2% since the adoption of electronic medical record (EMR) analytics. Moreover, by mapping EMRs to geographic information system data, Duke University has been able to predict specific ailments—such as influenza—that will spread in specific areas, allowing hospitals to stock serums and vaccines in advance.
As William Thomson said, “what gets measured gets managed”, and what gets managed gets better!
[i] KPI Examples. Scoreboard. Retrieved from here
[ii] Split Testing Optimizely: Split Testing Simplified. Retrieved from here
[iii] Lande, Stewart (2016). Seven Big Data Examples That Have Improved Healthcare Operations. Ingram Micro Advisor. Retrieved from here