In today’s competitive era Consumer Packaged Goods (CPG) companies must constantly evolve and rethink. This has been influenced by a number of factors like-
This has forced the CPG companies to look out for disruptive technologies like IoT and Data Analytics to devise a winning strategy and gain a competitive edge in this cut-throat environment. Here are some trends in data analytics for 2018 that will help CPG companies to win over the competition.
1. Reverse Logistics Analytics- A recent survey revealed that 97% of executives understand how data analytics can improve their supply chain but only 17% have implemented analytics in one or more supply chain functions. SCM is all about delivering the right product to the right customer at the right time at the right price. But one of the most prevalent problems in a supply chain system is to determine how many spare parts to manufacture and stockpile. Traditionally companies have used historical data to forecast the numbers. But new age analytics can help organizations devise a framework which can use data collected in real time from IoT devices integrated with products to predict failures accurately. This allows them to gauge precisely how many spare parts they need to stock.
2. Brand Analysis- Brand is the promise that the company makes to its consumers. It’s very important to build the right brand perception in order to take advantage of brand equity. It’s imperative to gauge the brand perception continuously so as to take remedial steps in case of any mismatch between the expected and desired perception.
Analytics can help to investigate the brand perception by assessing the negative and positive opinions from social media, blogs, news feeds regarding the firm and highlight the locations with negative brand perceptions. This eventually helps the firm to get a real-time understanding of their brand based on which they can take corrective measures for the promotional strategy of the company.
3. Route optimization-Logistics is an inherent part for CPG companies. Every company has an ultimate objective to reduce overall cost and observe faster transit time. Analytics can help create a dynamic route optimization model by using the historical data of the routes, costs involved, traffic situation, physical location of the destination, vehicle configuration, load to be carried through which the company can determine the most optimal route and the configuration of the transportation method to be used for deliveries.
4. Staff Analytics- Workforce is the spirit of the organization and by managing the staff effectively and ensuring their safety the organization can grow by leaps and bounds.Analytics can help in a variety of areas in the staffing domain. It can identify key factors and behaviors impacting the safety of workers which can help in making operational changes and safety compliance program to minimize safety risks.
Analytics can also help in workforce planning. By utilizing the information related to personnel, customers, work and finance the company can drive evidence based decision making to gauge the type of workforce required in the upcoming 5 years.
5. Product development through data based insights- A number of CPG companies are deploying IoT framework for improved preventive maintenance. Companies are also increasingly collecting feedback from its customers. Predicitve analytics can structure this feedback information coupled with machine data to generate patterns and trends. Suppose a company receives negative reports from both machines and customers about its product over a period of time then the company can collect the data about the product and culminate such an aggregation to a range of insights that can be used to modify and develop the particular product.
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Artificial Intelligence | Nov 30, 2018»
Artificial Intelligence | Nov 30, 2018»
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