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Reflecting on conversations with customers over the last six months, it's clear that the global pandemic is not in our rear view mirror - it's baked into our data. In fact, data is transforming retail. But across the retail industry, many retailers are experiencing "interesting times" when it comes to demand planning. The pandemic has disrupted historical data planning and is challenging the expectations of senior executives as global trends start and stop abruptly.

These challenges can easily be broken down into two key areas. First, historical data has become incredibly complex. The smooth curve and predictability gleaned from historical data was obliterated over the last 3 years with the pandemic driving demand sky high and other SKUs to new lows. Additionally, the recovery back to normal has seen unexpected spikes and lulls in normality. Secondly, this disruption further segregated the perspectives of executives, data scientists and planners. Planners are using demand data, executives are using their gut and data scientists are making decision with analytical data sets. We are now farther from a unified view of demand planning than ever.

At Accenture, we believe that for effective demand planning, it is critical that everyone within the company is using the same data, and working from the same information. When a spike in demand emerges, think back to toilet paper during early days of the pandemic, or a market issue like inflation changing, interest rates rising, companies need tools to help them identify the demand spikes and address them with pricing changes or evolving distribution plans. Executives want products on the shelves, data scientists want the most accurate data to make better decisions, and planners want to make sure the distributors are happy. If companies are going to extract the value that they need to stay competitive, they need to focus on driving not just data quality but a new level of veracity that elevates the signals and reduces the noise.

Shipping data from twenty-four hours ago may no longer be relevant if a port is shut down by the pandemic. Last year's seasonal patterns become less reliable in disrupted markets. The struggles around data quality are amplified for many retailers in their supply chain predictions, which by nature have the longest arc from signal to sale since orders may be placed months in advance. The siloed data, disruptions, and growing competition, while trying to keep an eye on overall sustainability, is an omnipresent obstacle that retailers are looking to overcome. With a process so complex, having a common set of facts and purpose built views for the key roles so that decision making can be fast, accurate and flexible.

Becoming a data-driven retailer

Retailers who will thrive in this ever-changing world will need to adopt a platform and strategy that provides total visibility, creating one version of the truth for their data. The solution will leverage internal data (e.g., from supply chain and trade), external data (e.g., consumption data, mobility, macroeconomic factors, brand sentiments, weather, COVID-19 cases) and advanced algorithms to forecast consumption. Retailers will be able to use this as their one point of truth – providing data that planners, data scientists and executives are looking for.

Over the last year, Accenture has been working with their customers to solve for this. Based on the recent launch of the Databricks Lakehouse for Retail, Accenture has created a Unified View of Demand solution that is an open, glass-box approach to demand planning. The Accenture solution is part of the Brickbuilder Industry Solutions program. With this solution, clients can increase forecast accuracy, speed and granularity, while shifting from debating forecasts to input alignment.

Value realized

Accenture worked with one global CPG company facing multiple challenges for demand forecasting, based on consumption and shipment forecasting models. The customer was able to implement the Databricks Lakehouse Platform, solving for unconstrained demand and shipment forecasts. The solution also helped the customer standardize their way of receiving base price, average discounts, integrating the streamlined forecast to supply chain and finance. After Accenture set up Automated Demand Sensing utilizing the Databricks Lakehouse Platform, the client was able to generate weekly forecasts with 10-15% accuracy improvement. This bias improvement of 5-10% helped the supply planning team with better inventory planning and production schedules.

As companies look to prepare their data and AI strategy for the future, they need to keep in mind that retail is on a transformation journey, starting with their data.

To learn more about Accenture Brickbuilder Solution, Unified View of Demand, click here.

To learn more about Databricks' Lakehouse for Retail, click here.

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