Page 8 - EngineerIT September 2021

DATA ANALYSES

Disrupting the supply chain are opening, as well as new challenges,”
says Breedveld. “The artificial intelligence
of things (AIoT) is also adding new
opportunities and challenges. More data
with better data analysis is available from both inside and outside
the organisation, whether a retailer or
otherwise, understanding has increased
around the value of analytics in the supply
chain, and more analytical processes
hursday, 26 August 2021 - According to the SAS Experience 2030 research, 65% of are available. Therefore, adoption is
South African consumers have indicated that they will not be returning to traditional increasing, but slowly.”
Tshopping practices following the onset of the COVID-19 pandemic, with 37% of those Modern supply chains are really
stating they will use even more online and digital apps than they do currently. This is putting networks of incumbent and potential service
significant pressure on supply chain planning and logistics as organisations must ensure providers, all of whom produce a range of
products arrive on time and deliver a quality customer experience. data that is both incredibly complex and –
Ronald Breedveld, senior retail and CPG director - business advisor, SAS Institute, if harnessed correctly – can form the basis
France, and the company’s expert speaker at the recent SAPICS conference, says the old for quick and simple decisions to ensure the
ways of operating businesses will not succeed in the future given how consumer buying sustainability of a business.
patterns, the supply chain and logistics are all subject to significant and rapid changes in the Demand sensing, trend analysis, and
highly connected world. pattern recognition can be leveraged
“A key component for retailers is accurately forecasting short-term consumer demand to daily to make decisions about how, when,
ensure that their products are available to consumers when they need them,” says Breedveld. and where to send goods to optimise
Implementing a short-term (one-to-eight-week) forecast is critical to understanding and replenishment, improve inventory levels,
predicting changing consumer demand patterns associated with sales promotions, events, and maximise availability on shelf where
weather conditions, natural disasters and other unexpected shifts (anomalies) in consumer demand is highest. Pattern and trend
demand. “Short-term demand sensing allows retailers to predict and adapt to those changing analysis allows for quick decision-
consumer demand patterns and has become an imperative for success in the local operating making in responding rapidly to changing
environment,” continues Breedveld. consumer buying patterns.
This is where a machine learning (ML) approach to creating these weekly and daily short- Breedveld indicates that business
term demand forecasts becomes invaluable. Using this approach, combining segmentation value is increasingly driven by the volume
analysis, ML and traditional time-series forecasting models, retailers can generate improved of satisfied and repeat customers. “The
forecasts by using historical supply signal (shipments) data in combination with point-of-sale pressure to get the right product to the
data (demand signal), sales promotions, trade inventory and others. right place at the right time at the right
“Fundamental to all this is effectively managing the explosion of data being generated by cost is even higher than it has been
the myriad of touch points. The vast network of connected sensors and involved devices is before. The people who turn that big
altering the way that we think about supply chains and how they are managed. We can now picture into executional reality are supply
see much more about what is going on, and that inevitably means that new opportunities chain leaders. This is increasingly the
case as value chains become more
network based. We are in an age of
instant gratification and as a result, board
members are increasingly turning to those
executives who can change strategies into
executional reality.”
The Experience 2030 research also
found that 16% of customers globally have
switched service providers for faster or
more convenient delivery options and a
further 13% changed providers due to a
negative customer experience.
“Today’s long, complex supply
chains generate huge amounts of data.
The importance of understanding the
supply chains and gauging how resilient
they are have been brought into sharp
focus by the pandemic. Analytics helps
organisations to make sense of this
data and make sure organisations fully
Modern supply chains of the future will be digitalised, data-driven and look to harness the understand what is happening and how
power of machine learning and artificial intelligence to optimise processes and operate at best to adapt to customer demand,”
previously unthinkable levels of precision. concludes Breedveld. n

EngineerIT | September 2021 | 6