Retailers and CPG manufacturers will have to continue to address the key dynamics of increased demand volatility and the step change in omnichannel purchases, which have created a number of challenges, including ensuring product availability for high customer service and executing strategies to manage risks due to demand surges and supplier disruptions.
In particular, the landscape is being challenged by a number of fundamental drivers:
- The changing consumer preferences with the move towards fresh, natural/organic/healthy, convenience foods and locally sourced products while looking for value.
- For retailers, a significant shift in channel preferences with the need to support various store formats and omnichannel options.
- For CPG manufacturers changing volumes from modern trade (hyper/supermarkets) to, e.g., discounters and e-Commerce.
- The need to respond to those changes while maintaining margins, service, and efficiencies with optimal inventory, sourcing, transportation, and fulfillment planning.
As a recent grocery retail study by McKinsey(1) points out, “the growth of online and the trend toward value are likely to put further pressure on grocers’ margins, especially given that the overall market may shrink once restaurants return.”
These transformational shifts in consumer behavior create unprecedented levels of variability, uncertainty, and complexity in supply chains. Retailers are forced to challenge the status quo and step up their supply chain competencies to transform their businesses successfully. CPG manufacturers scramble to strengthen their connection with consumers and, in some cases, bypass retailers altogether. There is a realization that running an exceptional supply chain takes a commitment to leverage data and advanced analytics to make intelligent, fact-based decisions while continuously evolving product offerings, supply chain strategies, and execution capabilities.
Retailers and CPG manufacturers have realized that they need to upend their traditional operating model with a digital operating model so that they can quickly analyze, optimize, and evaluate complex decisions before taking action. Getting to this new operating model is a transformational journey with great promise in delivering greater confidence and control over business outcomes.
Houston – We have a supply chain problem
No matter how well retailers and CPG manufacturers plan their product portfolio or assortments available across both physical stores and the online channel, forecast demand using sales or shipment history with internal drivers (promotions, digital coupons, social media campaigns….) as well as external drivers (weather, interest rates, new housing starts….), and carefully procure and place inventory, they constantly face operational issues during execution. Promotions and markdowns do not yield incremental sales as planned, there are subtle changes in consumer preferences across channels, suppliers have material or component availability issues, and transportation bottlenecks disrupt and cause targets to be missed and lead to a host of issues like out-of-stocks, too much inventory and dissatisfied consumers.
Controlling business outcomes with supply chain control towers
As the great boxer Mike Tyson said, “Everybody has a plan till they get punched in the mouth.” The planning organization may have the best-laid plans. Still, the sheer volatility in the operational environment requires continuous course corrections, with scenario planning and evaluating various competing alternatives.
Many retailers and CPG manufacturers are now looking at Control Towers and S&OE capabilities to address many supply chain blind spots, including unexpected supply shortages, network bottlenecks, response to disruptions, and big changes in what consumers are purchasing and where they are purchasing. Control Towers support sensing demand fluctuations and supply disruptions in real-time, translating that into various risks – the risk of poor customer service or the risk of lower revenues, or lower margins due to expensive course corrections. The most advanced Control Towers diagnose the root causes of supply chain failures and prescribe several corrective actions along with their costs and tradeoffs.
The emerging best practice is to deploy cognitive control towers that are both analytical and operational. They not only provide end-to-end visibility from consumer purchase to supplier shipments but also provide recommendations on what to do that address issues and enables users to choose from various options and act on them.
These control towers address the 3Ws of decision-making: What happened? What is likely to happen? What actions need to be taken?
Retailers and CPG manufacturers increasingly struggle with getting the insights they need to answer these questions during planning and execution. This costs them billions in value leakage – lost sales, consumer dissatisfaction, increased supply chain costs, excess inventory, and lower organization productivity. Not to mention the adverse impact on the planet due to poor utilization of scarce resources by (global) supply chains
Making control towers cognitive
Artificial Intelligence (AI) and Machine Learning (ML) techniques have emerged as critical enablers of the 3Ws and provide cognitive capabilities to control towers. AI/ML would have limited value if the item the consumer wants is unavailable, if an order promised for store pickup (BOPIS) is not ready in time, or if additional promo volume cannot be fulfilled.
- What happened? ML techniques provide Diagnostic capabilities and can identify the root causes of fulfillment failure. There could be one or a chain of root causes that lead to service failure – items not in store and must be procured from a regional DC with bad lead times, workforce unavailable for BOPIS orders, missing items at pick locations, limited pickup window duration for customers, supply disruptions at import DCs, excess number/variety of things in the order or inadequate retail store or warehouse space.
- What is likely to happen? The Predictive capabilities of ML are ideal for understanding the effects of forward-looking demand drivers to forecast a demand surge at a specific region, perhaps due to local events, social media buzz, unusual weather, or competitor supply disruptions.
- What actions need to be taken? AI/ML can provide Prescriptive recommendations with an effort or a sequence of steps to various roles in the supply chain so that fulfillment execution, manufacturing, or properly changed plans are ensured.
Control towers Power the Monday morning jumpstart
A familiar story at many retailers and CPG manufacturers – When Monday morning arrives, the merchandising, operations, and planning teams are frantically piecing together the previous week’s performance. They scramble to put together the net sales revenue and volume sold by department and region, measure the effectiveness of promotions and markdowns, identify items that beat their targets or underperformed, uncover inventory issues and assess capacity (e.g., labor) shortages. A lot of blood, sweat, and Excel is devoted to root cause analysis of operational failures. This weekly ritual involves teams from every corner of the business, often takes up a full day (or two), and frequently does not deliver the answers needed to take action for the current week or anticipate issues in the subsequent week.
Now, imagine Mondays are driven by knowledge and insights from a Cognitive Control Tower. By the time the teams arrive in their offices, the control tower has done all that number-crunching, highlighted exceptions, and served up recommendations to address sales weaknesses, reduce stockouts, leveraged excess stocks and risks of obsoletes, and adjust purchase orders. Instead of Monday morning debates over conflicting numbers and pointing fingers, retailers get action-oriented recommendations to move forward immediately and more time to focus on making decisions to delight the customer and consumer.
While the above may sound like a dream that is many years out, many retailers and CPG manufacturers in the grocery, apparel, electronics, beauty, luxury, and food & beverage segments are already using the 3Ws to drive significant improvements to their businesses. They can layer AI/ML systems on top of existing platforms to create control towers and leverage existing investments to deliver insights and decisions in a matter of months — without the need for multi-year transformations or science experiments that do not scale beyond pilot efforts.
1. The path forward for European Grocery Retailers, McKinsey & Company, March 25, 2021
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About the author
Vikram MurthiVice President Industry Strategy
Vikram Murthi, Vice President of Industry Strategy at o9 Solutions, engages with companies to understand their merchandising and supply chain challenges and helps shape their investment strategy and transformation roadmaps. He has extensive experience in supply chain transformation initiatives focusing on business case development, strategic roadmap planning, leading client workshops and solution definition. Vikram is interested in helping consumer-facing businesses leverage Big Data, Artificial Intelligence, Machine Learning and Optimization techniques to improve merchandising, forecasting, inventory planning, omni-channel fulfillment and new product introductions. Vikram has a B.Tech in Electrical Engineering from Indian Institute of Technology (IIT) in Kanpur, India and an M.S. in Computer and Systems Engineering from Rensselaer Polytechnic Institute.
Stijn-Pieter van HoutenVP of Industry Solutions
Stijn-Pieter is VP of Industry Solutions at o9 Solutions. He has over 13-year consulting career in Supply Chain Strategy and Transformation and a keen interest in Planning and Control Tower topics.