Ending Supply Chain Whack-a-Mole Management

Working to optimise Retail & CPG Supply Chains often feels like a life-sized and frenetic game of Whack-a-Mole. Making a change here creates an issue there – and another challenge then pops up somewhere else. At the same time as Supply Chains lengthen and become more complex, customer behaviour is changing with increasing speed across a wider range of parameters, and those pesky burrowers pop up in more holes faster and faster than ever. Furthermore, that was the case even before the COVID-19 pandemic turned up the speed and volume still further.

Over the past decades Retailers & CPG’s have spent many millions on IT and data systems in efforts to spot the moles earlier and to hit them quicker. However, despite this, they are facing the same old challenges of “not enough of the right stock in the right place, and too much of the wrong stock in the wrong place” that they had 30 years ago. All the while, Supply Chains become significantly more complex and diverse, meaning that there are more moles and more holes that need to be whacked, resulting in companies buying newer “go faster” mallets. The game must change.

It’s clear a new approach is needed to manage Supply Chains in the fast moving, increasingly digital, Retail & CPG environment. The benefits are significant, with Gartner predicting more than $2 trillion in additional customer value through AI in the Supply Chain – but the only way to realise this value is to do something transformational, rather than trying to simply whack the moles faster and faster.

To succeed now and in the future in a highly volatile digital Retail & CPG environment, Supply Chains must be based on fully integrated, real-time data that can be used not only to inform decisions, but to automate actions. Analytics will drive all Supply Chains, with AI and Machine Learning algorithms managing the vast majority of decisions and transactions.

Analytics will not replace humans. Instead roles in Supply Chains will evolve to be less focused on the day to day execution, reporting and data manipulation, and more on forward-looking strategies, scenario planning and other value adding activities. With Machine Learning handling routine data analysis and execution, the focus can shift to fine tuning the Supply Chain to be more agile and resilient.

Customer behaviour, by its very nature, can be unpredictable and move quickly between extremes even in ‘normal times.’ Anything from a heatwave to a pandemic, or a new advertising campaign to rising unemployment, can and will significantly impact demand and supply. However, scenarios can be simulated and tested, both predictable events and potential ‘what if’ events. Suddenly Supply Chain management is no longer predominantly about balancing cost and service – but about investigating new ways to add value by becoming even more resilient, responsive and customer-centric.

Does a papering over the cracks approach sound familiar? As markets shift and product demand and mix change, operational systems are always in flux and in catch up mode. The rules and parameters used to configure and tune the systems can therefore be quickly out of date. This often results in poor outcomes from the current systems and teaches the end users to mistrust their outputs. As users are forced to spend valuable time manually tinkering with outputs to get the results they need, the more out of tune the systems become. Which leads to more tinkering and more work-arounds. Before you know it, this has become the de-facto way of working; essentially papering over the cracks.  It is no wonder that despite having increasingly capable systems than ever in place, Retail & CPG Supply Chains still struggle with same challenges they did 30 years ago. Significantly, a shift in mindset, as well as a shift in approach, is therefore required.

By using Advanced Analytics in Retail & CPG Supply Chains, you can quickly predict and highlight where trends in demand, customer behaviour, warehouse stock or a hundred other measures are starting to diverge from expected thresholds. These can be automatically flagged as real-time alerts.  Not only delivering the information in time to allow actions to be taken to prevent potential issues, but also used to automatically model the business impacts of these exceptions, suggest the best responses and, importantly, changes to the configuration of the operational systems. This keeps the operational systems in tune with the shifting business demands, maintains trust in the outcomes and reduces manual effort in managing the day to day operation.

Freed from the day to day transaction management, Supply Chain analysts can focus on tuning models and playing out scenarios to build resilience and agility into the Supply Chain. Better still, if they have access to data from across the whole business at their fingertips, they can not only plan and execute rapid changes to meet new and emerging needs, but model the impact of those changes before the implementation stage.

Orchestrating Supply Chain end to end data and managing it as a whole rather than a collection of point solutions, in real-time and at scale, unleashes the power to drive out cost and create additional business value. Agility and responsiveness to the demands of an increasingly digital Retail & CPG environment with new and rapidly evolving operating models can only stem from improving analytics first ways of working. It is not enough to be the fastest and most accurate Whack-a-Mole champion. Powered by data and driven by analytics, tomorrow’s Supply Chain leaders will transform the game entirely, and with it their importance in the Retailers or CPG’s business.