If retailers were starring in a movie this holiday season, it would be synonymous with the classic Tim Burton musical, The Nightmare Before Christmas. After two years of a pandemic that shook the retail industry to its core and urged retailers to dramatically enhance their online presence, diversify their delivery options and wrangle massive disruptions due to closed manufacturers or congested ports, this holiday season was supposed to be the light at the end of the tunnel. However, an inventory glut and resulting cash flow issues, inflation that rose above the predictions and emerging eco-consciousness on the part of consumers are three key factors shaping the current retail landscape.
Retailers today must be agile to survive and grow market share, and new technology plays an increasingly important role. In the software space, the “waterfall” methodology has traditionally been used by many organizations. Clients and development teams would spend months — if not years — defining the specifications of the system before it was developed and implemented.
The problem was that during the time it took between kickoff and deployment, the processes that were originally defined had changed and evolved. For that reason, many businesses shifted to an “agile” software implementation approach to capture critical changes along the development path.
With the world in a constant state of change, what matters most to retailers is to have a solid and realistic software deployment plan in place, monitor it in real time and then be ready to adapt versus creating a perfect plan and sticking to it no matter what. If you’re ready for this type of approach, here are a few things to consider:
Any retail planning process starts with predicting what consumers want and where they’ll buy it. The first step in driving agility is automating the demand planning process. Indeed, as the diversification of SKUs keeps expanding, it is important for retailers to automate the calculation process.
This first involves ingesting a variety of data, from internal data like pricing and historical promotions; external data that includes demographics, inflation and interest rates, disposable incomes and more; historical data such as shipments, POS sales and the like; and forward-looking data such as weather information. It’s key to incorporate all of that information into algorithms that will provide a forecast with a higher level of accuracy than if it was only created using historical data.
With such technologies, retailers will be able to streamline the forecasting process, allowing their teams to focus on execution and decision-making. This is important because it allows teams to account for external factors or unpredictable events and to course correct in order to mitigate their impact on the business.
Digital Twin and Control Tower
Beyond algorithms, technologies such as a Digital Twin are highly beneficial for retailers to manage their operations. A Digital Twin is a virtual representation of a company’s physical supply network that models every resource, such as storage capacity, labor and transportation. The data from these different assets can be analyzed in real time. Coupled with the application of artificial intelligence techniques, these solutions will anticipate supply disruptions in real time, translating this information into risk analysis. The most advanced solutions diagnose the root causes of fulfillment failures and prescribe a number of corrective actions, along with the costs and tradeoffs to allow for fast data-based decisions.
Demand Sensing and Shaping
In order to remain agile, retailers need to continuously monitor consumer demand. However, their forecasts aren’t perfect. Being able to rapidly identify whether the forecast is under or over, as well as trend characteristics such as product cannibalization, product mix error, upcoming stockouts and more, is essential.
Machine learning algorithms that are able to provide root cause analysis by ingesting actual data (sales, traffic, etc.) and processing it against the forecast allow teams to focus on potential solutions and rapidly react to market changes.
If there is no option to place additional orders or to cancel upcoming ones, these solutions enable retailers to set up multiple scenarios based on the different levers that influence demand, such as price change or product placement. It then analyzes each one to understand its feasibility and impact on margins, such as cost-to-serve or store-demand fill rate versus cost tradeoff, in order to make the best decisions to achieve their objectives.
Last but not least, a critical lever to drive agility is reducing lead times. It’s not about retailers putting pressure on their suppliers to produce more quickly or for transportation to drive faster, but rather to streamline and enhance their collaboration with the suppliers. New collaboration platforms allow retailers to expand access to their suppliers and automatically share the forecast with them. From there, suppliers are able to provide their capacity and collaborate on production plans and raw materials requirements, as well as identify potential bottlenecks and risks early on to prevent disruption.
What the last decade — and more specifically the last couple of years — taught the industry is that the only certainty is uncertainty. The intensity of demand surges is only matched by the speed of its shifts. Although changes in the retail industry are constant, the pandemic and its consequences have been a catalyst for how retailers need to change their planning processes, and technology is a great area of opportunity to address existing constraints. Thriving retailers will create agile processes that can continuously align with changing trends.
Margaux Herbert-Saada is a Product Marketing Manager at o9 Solutions, With almost a decade of experience implementing supply chain software within the food service industry, she is passionate about innovative solutions that help companies improve their P&L as well as their sustainability. Anjali Burkins is a Retail Strategy Advisor at o9 Solutions. She helps prospective and current clients on their journey to digital transformation and delivering business results. She has held several merchandising positions at notable brands such as Tommy Hilfiger, Coach and Saks Fifth Avenue.