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Using big data for big improvements

02 March 2018

Richard Walters discusses how the effective analysis of big data can offer the opportunity for food and drink manufacturers to make a step change in operational efficiency and productivity. 

With the onset of Industry 4.0, significant strides are being taken in terms of the ability to capture and analyse data all the way through the supply chain.  

This big data is more than just process data. It describes the vast quantity of complex data sets that come from all areas, and from all levels of an enterprise and beyond. For the food manufacturer, its scope can be seen in three paradigms - manufacturing and factory based data; the up and downstream, or end-to-end, internal supply chain data; and relevant external data that has a material effect on supply chain performance.   

Within the food factory, data points are widespread, and connectivity between different machinery is vital.  Here, sensors are used to collect and provide real time information, examining production line downtimes and changeover intervals, temperature of materials, line productivity and overall equipment effectiveness (OEE). Turning this data into actionable information can help to optimise production assets, increase productivity, and reduce bottlenecks on the production line.  

Upstream, especially in raw material production, agriculture is taking a lead in implementing advanced technology to improve production efficiency. Today it is commonplace, for example, for agribusiness to use satellite data to optimise farm inputs and drive yields to a higher level within each field. The same technology platforms enable the harvest period to be optimised, minimising the need for post-harvest processes. The result is higher yields, lower costs and less waste. It also offers information that can be utilised by manufacturers to optimise factory performance and supply planning processes by gaining greater levels of knowledge on the status of incoming material – such as timing, frequency, volume and quality.  

Further down the supply chain, retailers are increasingly using big data to understand customer buying behaviour. Technology innovations include cameras in store aisles that scan shelves to look for out-of-stocks items. The outputs can be used by the retailer in enhanced demand sensing analysis, which in turn can be used to help optimise supply chain inventory management. Within the factory environment it can also be used to optimise production scheduling, helping to better manage staff numbers and shift timings to reduce staffing costs, for example.   

The recent WRAP report on food waste generated at farm level included a good example of a connected industry. An initiative led by ASDA and experts from the National Institute of Agricultural Botany (NIAB) began training growers to upload photos of crops using their smartphones. The images are interrogated by algorithms based on decades of scientific research, to convert the information into an early but accurate yield forecast.    Harnessing these diverse points of data and using advanced analytics platforms -often driven by, or through the ERP platform – can give a greater degree of insight into areas such as production scheduling and capacity planning and optimisation of the NPD process.  

The right technology platforms are needed to benefit from big data but, most importantly, it requires investment in people who will manage it. Having big data is one thing, making sense of it is another so it is vital to have the resources in place to interpret it.  An effective team to address big data projects requires experts in advanced mathematics, predictive analytics, high-performance computing and business knowledge.   

The real value of integrating and analysing big data needs to be determined on a case-by-case basis. It depends on the type of business, availability of data and technology, and the ability of the organisation to execute this kind of initiative.  

Conclusion
In the highly competitive food sector, big data analytics can provide a platform for the food industry supply chain to undertake the transformational step changes needed to enable businesses to continue to compete and standout.

Richard Walters is a manager at BearingPoint.  


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