How to increase business resilience in dynamic times via advanced forecasting and replenishment capabilities

Authors: Andreas Späne, Marco Tietze, Frauke Schleer van Gellecom, Yannik Knipprath, Alena Wenck

The complexities of global supply chains have surfaced over the course of the COVID-19 crisis, recent natural disasters, and geopolitical instability. Consumer demands shifted drastically, national borders closed, and suppliers’ operations were disrupted. Many retailers have learned a painful lesson in striving to adapt to environmental change – but the fear remains: What can be done to proactively anticipate the supply and demand shifts of upcoming disruptions to avoid stock-outs while keeping a lean inventory?

The new normal is about managing volatility, thus understanding drivers of uncertainty. Accurate demand forecasting and intelligent replenishment planning form two key levers in developing market foresight and building a robust supply chain. Hence, retailers should focus on advancing these strategic capabilities and make them an integral part of their digital transformation agenda. By modernizing the system landscape and breaking up the data silos, transparency across the entire supply chain can be gained and new automatization opportunities unfold. AI-based forecasting and replenishment (F&R) helps to identify and understand critical business drivers such as weather, prices, marketing expenditures and calendar effects and can provide near-time information about typically unpredictable demand shifts (“black swan events”) using Google Trends data and Sentiment Analytics. This allows retailers to elevate their forecasting accuracy up to 90 – 95%; thereby significantly improving profitability.

Today the market offers numerous advanced off-the-shelf software solutions, which can enhance F&R processes. But new technology alone usually does not solve the problem – it requires an organizational transformation. We have identified six success factors that enable your company to reap the maximum benefits of advanced F&R systems.

1)   Harmonize system landscape and data models

Nowadays, larger organizations often manage a complex landscape of IT systems, which has incrementally been enlarged and adapted due to changing requirements and updates. Hence, the first step in advancing your F&R capabilities should be the harmonization and standardization of the system landscape to create a robust technical foundation. By introducing one central Enterprise Resource Planning (ERP) system and a uniform data model, organizations can establish a “single source of truth” – the database that advanced F&R applications require.

2)   Leverage internal and external data assets

Many organizations underestimate the power and informative value behind the data sources they have readily available. These can and should be used to build sophisticated F&R models. From an internal perspective, marketing and promotion planning, store layout as well as location should be factored into a demand forecast. Furthermore, organizations can leverage external public data such as weather, prices or events: On a hot summer day with a popular football match the demand for BBQ products will peak. Consequently, these internal and external data sources constitute crucial demand influencing factors, which can significantly improve forecast accuracy.

3)   Establish clear data and system governance

Building a robust data foundation to feed F&R models is not a one-time effort but rather a continuous management task. Clear data quality standards must be set and measured across the organization to ensure a cohesive data base on which the models can be run. However, these standards must be institutionalized through a dedicated task force consisting of data stewards, who ensure a high level of data accuracy, completeness, and consistency. Moreover, a central unit accountable for the definition and maintenance of forecasting parameters and demand influencing factors should be set up. An overarching data and system governance with clear roles and responsibilities is vital for elevating data-driven F&R capabilities.

4)   Manage organizational change

Merely implementing advanced F&R systems does not guarantee success – process performance may worsen initially because organizational procedures and roles must be changed. Years of experience, implicit know-how, and best-practice formulas are replaced, stimulating organizational resistance. However, retailers rely on employees’ cooperation to exploit the systems’ functionalities. Their expertise is needed for precise adjustments such as exception handling, parameter refinement and finally, decision-making. Hence, retailers should adopt rigorous change management practices including mutual upskilling for business and Data & Analytics (D&A) teams, success story sharing, and new incentives. Most importantly, management commitment is crucial - the transformation should be business-led with D&A acting as a helping hand by guiding through playbooks to build trust in AI-based F&R. By creating transparency and actively involving employees, a positive mindset to change is established.

5)   Build an ecosystem with business partners

The full benefits of advanced F&R capabilities are not realized in isolation, but when harnessing them beyond organizational borders. Sharing the newly gained insights with business partners allows for end-to-end supply chain optimization. Suppliers and logistics providers can thereby plan production and transport operations further in advance to consistently fulfill your demands. In case of supply shortages or disruptions, business partners can communicate in a timely manner so that risk mediation measures can be activated.

6)   Become a self-learning organization

Developing F&R into a strategic capability is an incremental process. Once the technical implementation is completed, the new F&R systems and processes should be tested thoroughly to ensure operational continuity. Retailers might, for example, pilot an easily predictable staple product, and slowly expand to other product segments after its successful roll-out. During this process, it is key to reflect on experiences, derive learnings, and share best practices across the organization, so that different business units and stores can improve their performance.

In conclusion, recent crises have made retailers realize how important it is to hedge against uncertainties and highlighted the need for more transparency and advanced AI-based F&R. Accurate demand forecasting and intelligent replenishment planning are key levers in reducing stock-outs or excessive inventory levels. While new solutions certainly offer advanced functionalities, building a strategic capability in F&R requires more than a system upgrade. It involves an incremental transition towards a data driven organization comprising both technical and organizational elements. The scope of such a transformation should not be underestimated but helps in building future-proof operations and can significantly enhance business performance.

Feel free to get in touch with us to discuss and get insights on advanced F&R and end-to-end supply chain optimization and how they can be integrated into a successful transformation.