From an SCP standpoint, digital natives have one big advantage. They possess a wealth of consumer data that traditional companies don’t have. They communicate directly with their end user audience rather than getting aggregated second-hand data filtered through multiple retail channels. This data allows them to recognise market shifts much quicker and respond to demand variations but challenge is using this data to leverage their business model. Most companies have the data, but lack the tools to leverage it.
Another challenge is how to grow and scale at speed. Most of these companies concentrate first on the on-line customer experience, but at some point, they need to shift their focus on improving efficiency. They may have disrupted the market, but then need to compete on more classic business criteria such as profitability or return on invested capital (ROIC). They need planning competency to become efficient as well as automation and the productivity to scale. Smaller, fast growing companies need smaller but faster implementations.
Consumer goods businesses often have the opposite problem. Counting on the power of their more established brands, they have tuned their big-volume supply chains for efficiency, but when venturing into the DTC market they need to compete on the customer experience, not just customer service
Planning in a “one-at-a-time” selling environment is different. One of those differences is dealing with long tail, intermittent demand. Factors that contribute to the long tail are common in DTC.
- Product proliferation – DTC generally means a broader range of offerings. More products means splitting the demand between more buckets, so sales per SKU decrease. This translates into more intermittent demand and variability at the individual SKU level.
- More frequent replenishment – More frequent deliveries of smaller quantities mean that both replenishment and demand need to be managed in shorter time buckets, such as daily. Shorter time buckets mean much demand variability. An SKU may look like a stable “fast mover” if demand behaviour is observed in monthly buckets, but will look like a “slow mover” when observed in weekly buckets, and is likely to be intermittent at the daily level.
- Extended supply chain focus - While downstream demand visibility from the end-customer offers a more reliable demand signal, it’s dis-aggregated, granular nature increases demand variability and slow-moving behaviour.
Long tail demand calls for supply chain systems, processes and forecasting approaches with the ability to integrate, analyse and take advantage of detailed consumer data. For example, UK coffee seller Costa Express utilises machine telemetry feeds of real-time POS data from their self-serve coffee locations to drive demand, inventory and replenishment planning, significantly reducing field inventory stock and ingredient costs.
Direct-to-Consumer supply chain planning creates new challenges whether you come from a young start-up or an established competitor. The key is to overcome the limits of your firm, large or small, to address the unique capabilities required.
Click here to read the Costa Express case study.