By Khutso Maphatsoe | 13 March 2020 | Published on EngineeringNews
For fast-moving consumer goods (FMCG) companies to increase profits and remain cost efficient, value chain software company MACmobile believes that such companies need to consider merging artificial intelligence (AI) with the data generated in their supply chain.
Owing to the amount of data being created, stored and transformed into actionable insights, machine learning and AI will be required to run the logic and calculations.
MACmobile commercial director Andrew Dawson believes that, within a company’s operations, there are sections that can provide increased profits, but are not being explored.
“For example, you are running a distribution business and you have six distribution centres that distribute to 20 wholesalers, who, in turn, distribute to the retail industry. One of the wholesalers has sales on a particular stock that is consistent with 16 of its retail entities and the product is not being bought at four of the retailers because of religious, cultural or competitive reasons. If the distributor is not aware of this, the distribution centres will have ‘dead stock’ because the product is not being sold.”
Identifying the reasons for their retail market not buying a particular product will enable distributors to identify where profit can be leveraged or maximised rapidly by moving the stock into other centres.
“Having ‘dead stock’, or stock that is not moving in the distribution centre, is wasting money. That stock not moving or being sold will result in money being wasted. This is an area where data interpretation can make a difference on profitability,” he says.
However, Dawson points out that technology in the FMCG industry needs to be combined, as he has found that a software company can supplies a FMCG company with mobility in the form of a mobile application running on a smartphone.
The processes and parties in the supply chain would generally translate to there being three sets of technologies in the supply chain, but they do not link from a data collaboration perspective.
The manufacturer typically runs a manufacturing resource planning solution that manages the production of stock. The distribution and warehousing typically runs a warehouse management solution and distribution management solution to manage inventory levels and fleet management. The sales and delivery and the face of the supply chain, typically runs some form of customer relationship management or order/invoice application to capture sales and deliveries.
All processes and software sit on top of some form of enterprise resource planning or accounting solution to run the financials.
FMCG companies need to delve into the merging of data from all segments of their supply chain using AI to historically trace data from the past three to five years to start maximising their profits, says Dawson.
Consequently, the companies could then overlay the collected data onto their forecast for the next year or two u sing machine learning, he adds.
“This will start giving clear ideas on trends and trend analyses, and that is where FMCG companies can become cost efficient – by understanding the various factors that form part of the market.”
Using technology will enable distributors to acquire feedback on all their products through the amount of data that is collected. “A trained professional might be able to identify the trends, but using AI will identify them much quicker,” he highlights.
Although there are various platforms available that can be used to collect and analyse data, the challenge is to synchronise the different data streams to work as one, Dawson concludes.