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    Consistency makes compliance: meeting regulatory pressure through AI

    19th October 2023 | 5min read

    = Summary: Ed Betts highlights the increasing levels of legal obligation faced by retailers and the path to ensuring compliance without failing customers =

    Retail pricing is an area that often comes under significant scrutiny. The cost-of-living crisis has brought the effects of inflation into sharp focus for consumers and puts pricing once again in the spotlight. The potential for profiteering and ‘greedflation’ has attracted significant press attention. And as certain business costs appear to be easing, retailers themselves harbour concerns over the wholesale prices which continue to be charged to them by suppliers.

    The uniting factor here is consistency: consumers need consistent information on pricing to make considered decisions on the products they buy; retailers need to be consistent with the labelling and promotion of special offers; and negotiations with suppliers must be held in a manner consistent with regulatory requirements to be fair and transparent.

    Any retailer looking for a route forward has a choice: work harder or work smarter. Given that the schedule of Joint Business Planning means such decisions are often made well in advance, it is vital to implement the built-in compliance of an algorithmic retailing approach early rather than fighting fires later.

    Compliance in unit pricing

    In a previous investigation, the Competition and Markets Authority (CMA) concluded that inconsistent and over-complex unit pricing can potentially prevent customers from discovering the deal which offers the best value. In the context of the current market, the CMA has resumed its investigation – and its July 2023 findings[1] suggest that little has changed.

    Although the Price Marketing Order (PMO) 2004[2] requires retailers to display unit pricing for most grocery products, the CMA finds its enforcement of specific measures to be ambiguous – and that its structure permits “unhelpful inconsistencies in retailers’ practices”.

    When the shelf-edge display of one product in a line displays a price per kilogram, a price per gram, and a price per individual item in a pack, it is very difficult for customers to determine which of these offers them the best value. When loyalty card pricing is promoted, the displayed unit prices often do not even fully relate to the eventual price the customer will pay.

    Future pricing regulations

    The CMA has highlighted its non-compliance concerns with many supermarkets, as well as recommending to the government a review of the PMO. It proposes changes including enforcement of a single standardised unit per product type, and clear unit pricing on promotional items.

    With such tightening of regulations forthcoming, algorithmic retailing is one way to find equilibrium on unit pricing. It consolidates every point of business data and can process and align it automatically. This means an algorithmic approach could, for example, identify product lines, run the required calculations, and adjust the unit pricing of each item to use consistent measures. It can also automatically produce unit pricing which follows loyalty card or temporary price reductions.

    Safely generating promotions

    Regulations regarding promotional pricing are even more stringent. All advertised discounts must consistently adhere to rules set out in the Consumer Protection Regulations, the Advertising Standards Authority’s CAP and BCAP codes, Chartered Trading Standards’ Pricing Practices Guide, et al. Advertising a non-compliant sale or promoting a product discount which is ineligible or cannot otherwise be fulfilled means facing serious fines.

    But planning these discounts – arranging on-sale dates, ensuring product availability, aligning with supplier discount periods, and meeting periods of high demand – is incredibly difficult, even more so since they must usually be cemented as the JBP is being prepared, without over-ordering if wholesale discounts are available.

    Again, with an algorithmic retailing approach, non-compliant discounts can be flagged at the planning stage, or even blocked outright. Intimate knowledge of the data, assisted by AI models running within custom-defined guard rails, also means an algorithm can offer additional insight into possible promotions – potentially uncovering new opportunities that a traditional planning process may have missed.

    Protecting suppliers through proper process

    High wholesale prices have some retailers considering their options. Some major grocery retailers have even requested that their suppliers reconsider their pricing in line with reduced energy and resource costs. This, obviously, must be done in a compliant manner, as a request rather than a demand, but if a supplier cannot meet the expectations of their retailer, the burden of compliance falls on the purchaser.

    Choosing to de-list a product must, under the terms of the Groceries Supply Code of Practice (GSCOP)[3], be done fairly, with genuine commercial reason, and with reasonable notice to the supplier. Failure to comply could result in fines of up to 1% of a large retailer’s turnover – considering the narrow profit margins that retailers operate under, such a fine could be extremely damaging.

    Algorithmic retailing can help to keep the de-listing process consistent and compliant with regulations. Highlighting those products which underperform or appear too expensive can bring such lines to light in a timely manner and allow the process of de-listing items to begin earlier than it would otherwise occur manually.

    The rate of inflation may be dropping, but it is yet to level off. This is a period of rapid change, happening under increasingly stringent regulation. An algorithmic approach is a smart approach which creates a consistent process structure, allows retailers to act fast, and automates the major burden of compliance, freeing key staff to make the decisions which will shape the post-crisis future of retail businesses.




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