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Delivering Food Safety insights using analytics

Business Intelligence (BI) has always been regarded as one of the cornerstones of corporate reporting. Its ability to gather information and present users with answers to key business questions has been a major asset to many businesses. But BI seems to be the preserve of the accountants and sometimes the marketing teams.

Delivering Food Safety insights using analytics

So why is BI not used by more food safety teams?

Food safety teams in many food businesses are no longer suffering from a lack of data; they are suffering from a lack of the right data. Think about the thousands of paper and electronic process and quality records, traceability records, internal audit records, completed process checks, customer complaints data, sales volume, intake records, etc.

QADEX has invested to ensure that all data across supplier risk assessment, supplier approval, raw material specifications, allergen validation, finished product specifications, goods in & QA checks, vendor scorecards, customer complaints management and product launch management can be used to drive insights. Initially these are achieved using business intelligence dashboards, with data analytics also possible.

Finding value in this data lies in the ability to analyse it and derive actionable business intelligence (BI). Food safety teams need the right big data to effectively define the strategic direction of their teams.

As we gather larger volumes of data, the challenge of ‘data noise’ arises and we need to be able to distinguish trends in these datasets to add business value.

By using cloud based machine learning and predictive analytics we can mathematically represent underlying relationships in current and historical data to produce predictions, forecasts or classification about future events. These technologies have enabled companies such as Mastercard  and Amazon to fight criminal activity by rapidly finding small, yet significant, patterns of fraudulent activity in huge volumes of data.

By now your eyes may be glazing over and you are asking how could any of these be relevant to food safety, in fact you may have already discounted this whole idea.

But wait!

What about using all of the customer complaint, sensory panel, QC data & production yield data to identify patterns & relationships which present opportunities to reformulate products with lower instances of customer complaints and production wastage. Small reductions in wastage and customer complaints can result in a significant improvement in business profitability.

Data analytics on product test results could yield insights and intelligence to identify emerging risks before they result in a serious food safety risk.

And finally, data analysis could yield insights which would help identify suppliers who are substituting or adulterating products. Using insights you could bring a new layer to your vulnerability assessments as part of BRC7.

All of the above are emerging opportunities which you will only be able to take advantage of if you have the data in a digital format, therefore we recommend starting to capture your data digitally as soon as possible.

Business intelligence tools are developing very quickly out of the realm of tools which you needed IT support to tools that can be widely used across your food safety teams.

Mobile BI

Gaining competitive advantage through a highly informed team is critical for success. For years, mobile BI has promised the delivery of easy to consume, accurate enterprise BI ‘anywhere and at any time’ – but only now is this becoming a reality.

Through smartphones and tablets, BI software can now empower mobile food safety teams with the ability to retrieve key data metrics using touch friendly, interactive dashboard interfaces. The result is a more productive team that is able to make faster, more informed decisions wherever they are.

Examples could include:

Internal auditors on the factory floor reviewing a specific production process could see the history and trends of customer complaints, non-conformances & lab test results relating to a specific process being audited and use these insights to probe deeper in the audit. The outcome could be the identification of hitherto unknown root causes which if addressed result in substantial improvements in quality metrics.

Hygiene auditors seeing the micro results for a process being audited and being quickly able to slice and dice the results by line, shift, team leader, chemical supplier etc to identify discernible patterns.

The above examples could be expressed as using data analysis to confirm gut feelings, for example you may feel that a certain team are not committed to hygiene but are ticking all the compliance boxes.

Self Service BI

QADEX customers using our BI dashboards know the power of the dashboards but also know that to update or reconfigure the dashboards requires the support of an analyst. As food safety teams use these dashboards more they continuously demand more from the dashboards and in shorter timescales.

Self Service BI (SSBI) can provide end users with the tools to create personalised reports and analytical queries – allowing them to take data from multiple, sometimes disparate systems, and integrate it all together. These user defined ‘mash-ups’ save time so that answers to business critical questions can be found quickly.

SSBI is for all departments, including technical, so for example you could use SSBI to combine data from your QADEX system, your labs LIMS system, factory temperature data loggers, spreadsheets etc to bring all data together to provide insights and value that would previously have remained hidden.

Conclusion

Extracting food safety benefits from data analysis and insights will involve a paradigm shift in how some food safety teams think. This will take time. The tools have arrived and are low cost and easy to use. Digital data is required to feed these tools. The teams who adopt and utilise these tools will deliver substantial insights and food safety improvements and increased brand protection.

The challenge will be establishing enough case studies and proof for the cautious food safety teams to take the leap into analytics.

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