The Data Imperative: How Retailers Are Adapting KPIs to Today’s Market Pressures
Scott Felten
Incorta Business Leader | Delivering Live, Detailed Ops Data at Scale from Multi-sourced ERP, HCM, CRM, MES, etc. (Oracle, NetSuite, SAP, Workday, etc)
Focused Article: Adapting Retail KPIs in a Changing Market
In this edition, we explore how retailers are evolving their KPIs in response to unprecedented market pressures, from supply chain disruptions to inflation. This focused article connects directly to the broader theme of Flat Data by emphasizing the importance of efficient and agile data strategies. As businesses adapt to rapidly changing conditions, the ability to quickly integrate new data sources and leverage advanced analytics becomes essential for maintaining competitiveness and achieving key business outcomes. This discussion aligns with the challenges many of our readers face in navigating today's complex data landscape.
The Data Imperative: How Retailers Are Adapting KPIs to Today’s Market Pressures
Since 2017, the retail industry has faced a series of unprecedented challenges that have fundamentally reshaped how key performance indicators (KPIs) are measured and managed. These challenges have forced retailers to continuously reevaluate their strategies, shifting their focus to meet the evolving demands of the market. For example, the once-steady cadence of just-in-time inventory management gave way to the necessity of buffering stock levels during supply chain disruptions, dramatically altering how Inventory Turnover Ratio was prioritized. Similarly, the emphasis on Customer Lifetime Value (CLTV) evolved as businesses adapted to changing consumer behaviors driven by digital transformation and economic pressures.
As external pressures mounted, businesses had to pivot their focus toward different KPIs to remain competitive. During the pandemic, the priority shifted from maintaining high Gross Margin Return on Investment (GMROI) to ensuring adequate stock levels and avoiding stockouts, reflecting the immediate need to stabilize supply chains. Later, as inflationary pressures grew, the focus turned toward managing costs and protecting margins, requiring businesses to fine-tune their pricing strategies and optimize Average Transaction Value (ATV). These shifts in KPI priorities were driven by the need to respond to specific external challenges, whether it was supply chain disruptions, changing consumer behavior, or rising costs.
These evolving KPI priorities also necessitated significant changes in data strategies. As KPIs like Inventory Turnover Ratio and CLTV took on new importance, businesses increasingly relied on advanced data analytics, real-time integration, and AI-driven insights to support these goals. The traditional reliance on ERP systems and POS data expanded to include dynamic data sources like supplier performance analytics, predictive modeling, and customer sentiment analysis. This shift in data needs allowed businesses to respond more effectively to the external challenges they faced, ensuring that their strategies were backed by accurate and timely information. In today’s rapidly changing retail landscape, the ability to align data priorities with shifting KPIs has become essential for sustaining growth and competitiveness.
In the following analysis, we delve into 10 critical KPIs that have undergone significant transformation over the past few years. We’ll explore how the focus on these KPIs has shifted in response to external pressures and examine the evolving data priorities that have supported these changes. Each KPI tells a story of adaptation and resilience, reflecting the broader trends that have shaped the retail industry from 2017 to the present.
Inventory Turnover Ratio
2017-2020 KPI Story: Inventory turnover was optimized for just-in-time delivery, minimizing holding costs and maximizing inventory efficiency through lean practices. Data Story: Data management focused on using ERP systems, POS data, and WMS for real-time tracking, minimizing costs, and maximizing inventory efficiency.
2020-2023 KPI Story: Retailers increased inventory levels to buffer against supply chain unpredictability, leading to lower turnover ratios to avoid stockouts. Data Story: Retailers began integrating dynamic data sources, such as supplier performance analytics and external risk management platforms, to handle supply chain unpredictability.
2023-present KPI Story: Inflation increased the cost of goods, prompting retailers to balance inventory levels to manage higher carrying costs. Data Story: Retailers shifted towards AI-driven demand forecasting models, integrating financial forecasting systems with traditional inventory management tools to optimize inventory turnover and manage inflationary pressures.
Sell-Through Rate
2017-2020 KPI Story: Sell-through rates were managed to ensure rapid product movement, often driven by promotions and seasonal demands. Data Story: Sell-through rates were managed using internal data sources like POS systems, sales analytics, and seasonal trend analysis.
2020-2023 KPI Story: The focus shifted to aligning sell-through rates with unpredictable inventory availability due to supply chain disruptions. Data Story: The focus shifted to integrating real-time data from WMS, SCM systems, and customer sentiment analysis to better predict demand amidst supply chain challenges.
2023-present KPI Story: Inflation led to slower consumer purchasing, prompting retailers to use aggressive discounting to maintain sell-through rates. Data Story: Retailers relied more on e-commerce platforms and CRM systems to capture real-time consumer purchasing patterns, with competitive pricing intelligence tools used to dynamically adjust prices in response to inflation.
Customer Lifetime Value (CLTV)
2017-2020 KPI Story: CLTV was driven by customer acquisition through in-store experiences, loyalty programs, and consistent product availability. Data Story: CLTV calculations were driven by data from CRM systems, loyalty programs, and POS systems, focusing on in-store interactions.
2020-2023 KPI Story: Retailers enhanced digital and omnichannel experiences to adapt to pandemic-driven changes in consumer behavior. Data Story: Retailers integrated online transaction data, mobile app usage, and omnichannel CRM systems to enhance digital and omnichannel experiences.
2023-present KPI Story: Inflation eroded disposable income, leading retailers to focus more on value propositions and loyalty programs to maintain CLTV. Data Story: Retailers increasingly relied on sophisticated customer segmentation tools that combine CRM data with behavioral analytics and economic indicators to refine CLTV calculations.
Gross Margin Return on Investment (GMROI)
2017-2020 KPI Story: GMROI was maximized by optimizing inventory levels to ensure high profitability. Data Story: GMROI was managed using data from ERP systems and sales analytics tools to optimize inventory investments and profitability.
2020-2023 KPI Story: Retailers accepted lower GMROI due to the need for higher inventory and expedited shipping during disruptions. Data Story: Retailers increased reliance on expedited shipping data and supplier performance analytics, along with cost management systems, to maintain GMROI amid disruptions.
2023-present KPI Story: Rising costs further squeezed margins, leading retailers to implement price increases and cost-cutting measures to maintain GMROI. Data Story: Retailers utilized advanced financial modeling tools integrated with supply chain data and AI-driven pricing strategies to optimize GMROI despite rising costs.
Customer Retention Rate
2017-2020 KPI Story: Retention was driven by consistent product availability, competitive pricing, and effective loyalty programs. Data Story: Customer retention was enhanced using data from CRM systems, loyalty programs, and sales analytics, focusing on in-store engagement.
2020-2023 KPI Story: Retention strategies adapted to supply chain volatility, emphasizing communication and transparency with customers. Data Story: The integration of communication platforms with CRM systems became vital to maintaining customer transparency and satisfaction during supply chain disruptions.
2023-present KPI Story: With inflation reducing purchasing power, retention became more challenging, prompting retailers to double down on loyalty programs and personalized experiences. Data Story: Retailers leveraged advanced loyalty management systems and AI-driven personalization tools to offer tailored promotions and experiences to enhance retention despite economic pressures.
Average Transaction Value (ATV)
2017-2020 KPI Story: ATV was driven by in-store upselling, cross-selling, and promotions to maximize each transaction. Data Story: ATV was tracked and optimized using data from POS systems, sales analytics tools, and in-store promotion management systems.
2020-2023 KPI Story: ATV was impacted by the shift to online shopping, with a focus on digital upselling and cross-selling. Data Story: The shift to online shopping led to the use of e-commerce platforms and digital analytics tools, with CRM data driving digital upselling and cross-selling strategies.
2023-present KPI Story: Inflation led to higher prices initially, but as consumers adjusted, ATV stabilized or declined, with a focus on maintaining it through upselling and cross-selling. Data Story: Retailers began leveraging AI-driven pricing and recommendation engines integrated with CRM and e-commerce data to maintain or increase ATV.
Foot Traffic and Conversion Rate
2017-2020 KPI Story: Physical foot traffic and conversion rates were critical, driven by in-store experiences and promotions. Data Story: Foot traffic and conversion rates were measured using data from in-store analytics systems, POS systems, and promotional management tools.
2020-2023 KPI Story: Physical foot traffic declined, while online conversion rates became more important during the pandemic. Data Story: The shift to online shopping increased reliance on web analytics, e-commerce platforms, and digital marketing data to track and improve online conversion rates.
2023-present KPI Story: Inflation likely reduced foot traffic and online conversion rates as consumers became more price-sensitive. Data Story: Retailers integrated consumer sentiment analysis and location-based services with conversion tracking tools to understand and respond to inflation-driven changes in shopping behavior.
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Stockout Rate
2017-2020 KPI Story: Stockouts were minimized through tight inventory management and just-in-time ordering. Data Story: Stockout rates were managed using data from ERP systems, inventory management tools, and supplier performance metrics.
2020-2023 KPI Story: Stockout rates increased due to supply chain disruptions, with a focus on better forecasting and supply diversification. Data Story: The integration of predictive analytics tools with SCM systems became crucial for forecasting and managing stockout risks.
2023-present KPI Story: Higher costs and tighter budgets led to more conservative purchasing, potentially exacerbating stockout
issues. Data Story: Retailers increasingly used AI-driven demand forecasting and financial modeling tools integrated with supply chain data to prioritize high-margin and essential items.
On-Time Delivery Rate
2017-2020 KPI Story: High on-time delivery rates were achieved through predictable supply chains and logistics networks. Data Story: On-time delivery rates were maintained using data from logistics management systems, SCM platforms, and supplier performance data.
2020-2023 KPI Story: On-time delivery rates suffered, leading retailers to invest in more robust logistics solutions. Data Story: Retailers began integrating real-time logistics tracking and supply chain visibility tools to manage the impact of disruptions on delivery performance.
2023-present KPI Story: Rising transportation costs further challenged delivery rates, leading to cost-cutting measures and careful logistics management. Data Story: Retailers increasingly relied on advanced transportation management systems integrated with financial modeling tools to optimize delivery routes and manage rising costs.
Shrinkage Rate
2017-2020 KPI Story: Shrinkage was managed through effective loss prevention strategies, keeping rates low and controlled. Data Story: Shrinkage was controlled using data from loss prevention systems, inventory management tools, and employee training programs.
2020-2023 KPI Story: Shrinkage remained a concern due to supply chain disruptions, leading to enhanced tracking technologies. Data Story: Retailers integrated advanced tracking technologies and supply chain management systems to mitigate new risks introduced by supply chain disruptions.
2023-present KPI Story: Inflation led to reduced investments in loss prevention, contributing to higher shrinkage rates. Data Story: Retailers used predictive analytics to identify high-risk areas for theft or loss, deploying targeted prevention measures despite budget constraints.
The following matrix provides a different perspective on the same data, highlighting the evolution of both KPI Focus and Data Priority over time. Reading from left to right, you can clearly see how new data needs emerge each time a business responds to external challenges. Whether it's shifting from Lean Optimization to Cost Management or from Internal Data Focus to AI-Driven Optimization, the matrix illustrates the dynamic interplay between business strategy and data requirements.
What becomes clear from this analysis is the critical need for responsive and adaptive data services that can evolve alongside the changing dynamics of the market. As businesses face external pressures—whether it's supply chain disruptions, shifts in consumer behavior, or inflationary challenges—the ability to rapidly adjust, integrate new data sources, and apply advanced analytics is no longer optional; it's essential. To meet market demands and stay competitive, businesses require a data infrastructure that is not just dynamic but also agile, capable of supporting continuous transformation. The matrix highlights how critical it is for data services to empower businesses to quickly pivot, adapt their strategies, and remain resilient in an ever-evolving marketplace.
Conclusion
It seems clear that the last few years have been a period of significant transformation for the retail industry, forcing a rethinking of traditional KPIs. As we look ahead, the introduction of GenAI, hyper-personalization, and an ever-increasing shift into digital experiences are poised to drive even more profound changes. These advancements could further reshape how retailers measure success and respond to market demands.
The ability to adapt and innovate will be more important than ever. Retailers who embrace these technologies and leverage advanced analytics will be well-equipped to navigate the complexities of the future. If you’re looking to stay ahead in this rapidly evolving landscape, explore how Incorta’s Retail Analytics Solutions can empower you to harness the full potential of your data. Let’s continue the conversation in the comments about how your KPIs can evolve to meet the challenges and opportunities of tomorrow.
About the Author
Scott Felten has been a technology and thought leader in enterprise analytics for nearly 25 years. He has experience leading initiatives as a customer, a trusted consultant advisor, and as a business executive within leading technology vendors. He specializes in aligning modern data platforms with business strategies to drive faster insights and measurable ROI. You can schedule a free consultation with Scott and his team here.
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