Optimising the value chain key to driving profit for FMCG in challenging economic environment

By Andrew Dawson | 20 January 2020 | Published on ITWeb


The cost to serve, which is the cost associated with manufacturing a product and getting it from the manufacturer to the shelf for purchase by the consumer, is the single largest cost driver in the FMCG value chain. It is therefore a prime candidate for optimisation in order to reduce costs and increase profitability.


There is also additional cost involved in stocking and storing products if they are not selling, as well as not having sufficient stock ‘on shelf’ to meet customer demand. If customers are not buying your products, they are costing you money, and if customers are unable to buy your products, you are losing sales and revenue. This all impacts an already stretched bottom line and needs to be effectively managed.


Data analytics is the key to unlocking opportunity

In order to improve the management of stock and the value chain as a whole, it is essential to create a better understanding of retail sales data. Retailers have access to granular data regarding the rate of sale down to a ‘per store’ level, and there is a lot of value that can be unlocked here. By applying analytics to sales data, manufacturers can begin to gain insight into which products are selling in what regions and in what individual stores. They can even determine how fast a product sells, and whether people tend to purchase it on specific days of the week or at specific times.


Data analytics can also be applied to promotions so manufacturers can understand the actual impact of a promotion. For example, if a manufacturer reduces the price of a product to drive turnover, does this promotion actually result in increased profit or is it simply creating volume. This helps manufacturers understand volume versus value for more effective pricing analysis. With enough data, it is even possible to understand which products people tend to purchase together, so promotions can be more effectively bundled to appeal to consumers based on actual behavioural information. Both retailers and manufacturers can then gain a better idea of what products will likely work together for promotions and what the cost to benefit ratio will be of promoting them as a bundled offer.


Collaborating to better understand your customer

The level of granularity required for effective data analytics requires collaboration between manufacturers and retailers. In order to leverage opportunity for optimisation, it is imperative that retailers and manufacturers work together. With the economy as it stands, every party in the value chain is struggling. If manufacturers purchase data from retailers, this creates an additional revenue stream for retailers and a wealth of opportunity for manufacturers, resulting in a mutually beneficial arrangement.


If manufacturers incorrectly determine the rate of sale, they can end up with dead stock that does not move and costs money, or they may not manufacture enough, leaving retailers unable to fulfill demand. Analytics on the data is critical to avoid these issues. Once all parties in the distribution channel can understand what customers are buying and when, manufacturers can ensure production and distribution match demand. Retailers can then ensure their stock levels are optimal both in store and on shelf. When promotions are run, direct communications can ensure maximum share of wallet, while optimised back-end processes ensure enough stock is available to fulfill demand.


Once the basics are in place, it is even possible to overlay additional data such as holidays or significant sporting events, which will inevitably have an effect on demand for certain products. Even the weather can play a role, and should be taken into account in a comprehensive analytics solution.


The future is real-time, just in time

Sales in the FMCG space will always have peaks and troughs and the distribution channel must cater for this. Stock needs to be ‘live’ on shelves at all times, but excess stock that cannot be sold costs money and must be avoided. Balance is critical, and both manufacturers and retailers need to turn to science to start optimising the value chain and boosting profits.


In the current climate it is all but impossible to create more retail spend, because consumers have a finite and shrinking amount of disposable income. It is therefore imperative to find ways of optimising the value chain, including just in time manufacturing and distribution. If manufacturers are able to analyse their sales using actual data, they are then able to determine where opportunities might exist. Without real-time data, however, this becomes a reactive process. Being smarter is crucial.


The future lies in streaming analytics based on the current climate and live sales data and buying patterns. Harnessing the power of live data is the only way to effectively optimise the value chain and therefore survive and even thrive during challenging economic times.

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