Process mining analyses business event logs, providing retailers with a detailed operational map and revealing inefficiencies that, when resolved, significantly enhance operational efficacy.
This is a decade of change for the retail sector, and process mining offers business leaders a crucial opportunity to both deal with the challenges and grasp the opportunities. Online shopping is predicted to double this decade. Meanwhile, retailers face increasingly complex distribution and supply chain logistics, and need to optimise and adapt fulfilment operations to today’s new and more complex environment.
As consumers switch to lower-cost alternatives (80% are switching to smaller pack sizes and cheaper brands), there has never been a better time to reap the rewards of data integration and process mining in retail. The technology offers the ability to uncover ‘hidden’ opportunities to drive efficiency, improve returns, and pave the way for the adoption of technologies such as generative artificial intelligence (AI).
Process mining analyses business processes using event logs, to offer an end-to-end view of what’s really happening within a business. It’s therefore a perfect fit for the process-heavy retail sector.
Retailers often run thousands, or even hundreds of thousands of transactions and processes across multiple systems every day. Being able to bring all those systems together through data integration and then apply process intelligence, offers an immense opportunity.
Having process data available in a clear, easy-to-understand form offers a complete picture of how processes actually run, highlighting actions which can improve the way retailers work.
Why process mining works
Process mining works on top of existing systems, so retailers don’t need to ‘rip and replace’ their existing technology. This offers a useful vantage point for business leaders to fix issues. Data integration and process mining work like an MRI scan, offering a complete picture of how processes work, and identifying hidden value opportunities within systems.
One leading retailer was able to achieve a 31% improvement in shipment utilisation, thanks to process intelligence. Process intelligence enabled this retailer to take a top-down view and improve collaboration between different teams in supply planning, transportation and distribution. The company used process intelligence to minimise the number of trucks sitting idle, which cut transportation costs, and reduced road miles and carbon emissions, helping the company to achieve its ESG goals.
In the back office, process mining can also improve efficiency, helping to automate manual processes, and avoiding problems such as duplicate payments or unjustified discounts.
Foundation for AI
Mastering and understanding data is critical to adopting new technologies such as generative AI, and being able to have a 360-degree view of business execution is the stepping stone to adopting this valuable technology.
For example, French retailer Carrefour recently combined the power of process intelligence with the potential of generative AI. The retailer, which operates in 40 countries with more than 14,000 stores, is experimenting with using generative AI to compare quotes from indirect buyers, using ChatGPT combined with data derived from process intelligence.
The retailer reported that its proof-of-concept experiment could analyse quotes from buyers in just 10 minutes, rather than the 30 minutes it takes when done manually, potentially saving the organisation thousands of Euros.
Carrefour is now examining how to apply this combination of process intelligence and generative AI to other areas such as marketing and human resources (HR), highlighting the time and financial savings to be made.
Improving returns
UK customers returned 27% of clothing alone in the past year, bought from online retailers. With returns costing retailers billions a year, process intelligence can not only make the returns process more efficient, but also zoom in on issues that are causing customers to return items.
Process intelligence can enable retailers to ‘get ahead’ of the problems that lead to returns, while spotlighting and identifying the errors which result in orders being sent back or cancelled in the first place.
Swiss luxury retailer, Globus, used process mining to identify the root problem leading to returns at its businesses, finding an inefficiency lurking ‘between’ different systems which caused customers to return goods. Due to this hidden inefficiency, it was possible for one customer to reserve an item online, and another to buy the same item.
Globus used process intelligence to reduce the overall cancellation rate by 20%, and also introduced a logistics dashboard which enabled the organisation to visualise throughput times and return rates in real time.
For today’s customers, efficient returns are part of essential customer service, and sub-optimal service can drive customers away. Well-marshalled ‘reverse logistics’ in returns, driven by the insights from process intelligence, mean that returned products can be rapidly resold. This means businesses don’t struggle with overstocked and understocked items, while keeping costs for transportation, storage and handling of returns down.
A more efficient future
For leaders in the retail sector, the time to capitalise on the opportunities offered by data integration and process intelligence is now. Process intelligence not only helps to streamline business processes, but also forms a perfect step to embracing emerging technologies such as generative AI.
Crucially, it can also help to drive customer satisfaction in areas such as returns. With retail in flux as online shopping booms and cost-conscious consumers shop around for bargains, process intelligence offers a tool to help retailers stay ahead in a fast-moving world.
About the author: Rupal Karia was recently appointed Country Leader UK&I at data processing company Celonis.
Source from Retail Insight Network
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