Challenges in delivering an exceptional customer experience consistently, through each market channel, come from all aspects of a business: soft (organization, processes, culture) and hard (systems, people, other resources). Addressing the challenges must encompass all soft and hard aspects and require process, organizational and cultural change as well as infrastructure investments.
Requirements: It starts with deliberate, conscious decision-making on what should be the customer experience delivered across customer segments and channels. Putting the customer at the heart of every operation is a given, but it is never as simple as just that. Companies strive to achieve the optimum customer experience within constraints and variables that drive increased overall costs. Ultimately, it demands bringing several channels to a common denominator, managing the number of operational and product variants, using the various channels as “correction valves” to balance overall demand and supply, and at the same time deriving what is best in each channel.
Resources: Defining the optimum balance between customer experience and operational cost will also highlight the talent and skills required to achieve excellence across all disciplines, from the initial customer engagement to managing the deep tiers of supply. Streamlining channels and fulfillment options results from functional omnichannel rethinking and reengineering, requiring methodology, skilled resources, and tools. Very few companies have these in-house. It is not their core competency, nor should it be. A natural solution is to adopt a standardized, proven and repeatable approach, one example being the Capgemini Industrialized Operations Platform, already tested and trusted by many clients.
Processes: Process transformation and standardization – supported by the right people – is only one side of what is required to ensure omnichannel performance optimization. A solid understanding of demand, supply, and engagement within each upstream and downstream supply chain tier can highlight the necessary changes in processes and organizational structures. Real optimization – whether for customer experience or any other combination of corporate goals – is only possible based on the knowledge of what the customers want and what the company can deliver in an economically feasible way. Brands can build this understanding by securing access to decision-grade data from all channels.
Data: The necessary decision-grade data spans several areas: inventory, sales, forecasts, demand, supply, logistics, and external influencing factors across all distribution and fulfillment channels.
The right data provides in-depth visibility into inventory across all tiers of distribution for each channel, including outsourced channels. This includes tier 1 inventory, regional distribution centers, and even store-level inventory, as well as all stock at a retail store’s multiple tiers of resellers.
The logical extension to channel inventory data is gaining inventory visibility across the multiple tiers of logistics and supply. Knowledge of supplier inventories is the first step in quickly shifting between providers when supply is constrained. Visibility into products and parts in transit simplifies fulfillment decisions.
Applications: Overall, inventory visibility at the finished product and part level, combined with demand data across all market routes, is great but delivers little value without insights to drive the followup. Data leads to insight, which leads to action.
Adopting the most efficient and scalable application as the standard to automate order intake and return operations for all channels is essential, although inward-focused and therefore not enough of a driving force for complete optimization of processes or performance. Optimizing omnichannel performance requires advanced applications with embedded analytics and AI, spanning the end-to-end supply chain via seamless integration.
Analytics provide a deep understanding of threats and opportunities to improve customer experience and corporate performance. AI embedded into collaborative applications that reach beyond the enterprise boundaries can interpret and trigger action on the data.