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It's time to overhaul merchandizing

Core merchandizing has arguably been the most stubborn of functions to transform in retail. Other parts of the supply chain and even logistics are undergoing drastic changes primarily due to the impact of COVID-19 and the unbundling of monolithic functions such as order management and warehouse management . While end-customer-facing capabilities are in a constant cycle of evolution and improvements – core merchandizing activities like forecasting, assortment planning, allocation processes and promotions, are in limbo. The business case for modernizing merchandising is still under construction and consideration at a majority of retailers. 


True pioneers however, have taken a more forward-thinking approach to unbundling the merchandising function, having realized its true potential and value as the heart of good retailing. 


Here are a few key imperatives accelerating a paradigm shift in merchandizing:


Expanding O2O influence  


In 2016, Jack Ma, Alibaba’s founder, introduced the term, ‘New Retail’ to describe a future where technology and the ability to leverage huge quantities of data will permit the merger of online, offline and logistics to create a dynamic new retailing era (also known as ‘O2O’). 


Today’s omnipresent customer requires a unified view across channels. Digital retail natives have shown the impact of online-to-offline thinking especially in the innovations to the physical store - its role in product discovery, experience and order fulfillment. 


The unified customer view demands a similar rethink of merchandizing as well. Category managers and merchants can no longer subscribe to siloed thinking since customers have moved to social channels and seek influencers for education, engagement and new age experiences.


Unbundling of core retail functions 


This general trend has impacted retail merchandizing where the traditional category management function is viewed as a conglomeration of several critical activities – budgeting, assortment planning, range planning, allocation, pricing,promotions and markdowns. The traditional approach partly contributed to creation of monolithic tools and rigid processes – a challenge for category managers to disaggregate and unlock value from. 


In contrast, digital organizations have been more agile in domains like search, pricing and promotions through dedicated focus backed by agile tools and methodologies. This has resulted in grabbing both customer mindshare and wallet. For instance, Thoughtworks has helped global retailers unbundle core functions (pricing, promotions, etc.) from large monolithic retail enterprise systems. This has unlocked efficiencies and has enabled nimble data driven decision making for category teams.


Advancing speed and specificity in planning and execution


Fashion and trend cycles are becoming shorter leading to an explosion of options for the customer. Category managers are compelled to sift through large volumes of data, distill insights and react at warp speed. Much of everyday work and analysis is still done using spreadsheets and most large, legacy retailers have developed highly customized tools to address specific challenges along their journey, which has, unfortunately, created multiple sources of truth within the enterprise. 


For example, it is not uncommon for category managers to use different data sets to plan their promotions while finance teams use another. In fact, most category managers spend a disproportionate amount of time trying to validate data accuracy. They use spreadsheets to analyze, share and communicate with both internal teams and their vendors. This leads to friction, manual work and loss of valuable time that could have been spent in deriving customer insights or planning better strategy and execution tactics  with suppliers. 


Forecasting and planning have become more complex given the newer fulfillment models, touchpoints, changing consumer tastes and dynamics of the post-pandemic world. The need to improve forecasting is not limited to extrapolating trends for the future but also being able to simulate, predict and prescribe such forecasts with precision. 


The days of channel-specific forecasting are over given the increasingly omnichannel nature of retail experiences and blurring lines between online and in-store experiences. In addition, demand planners must understand what customers buy, when they buy, how they buy and what delivery options they prefer. These details need to be factored into granular, location-specific forecasts.  And, without the right toolset, solving for this need becomes an unrealistic uphill climb for most category managers.


Recognizing this, Kroger set up a 84.51° Forecasting Center of Excellence to bring together knowledge, experience and advanced data science to solve forecasting at a multiscale level. Its cross-functional nature, multiple modeling approaches and the use of cloud computing for data transfer enable smart retail decision making.

The merchant of the future 


Category managers of the future will operate more like category owners.  They will lead cross-functional teams of merchants, planners, product managers, marketers and even developers to build apps for an agile and scalable ecosystem. 


Retail businesses will have to rethink the merchandizing function and its place in the new world of commerce. We foresee category managers reworking their organizations to:


  • Focus on strategic planning

  • Keep negotiation, planning and assortment central to the function

  • Leverage data science to drive sales along with suppliers

  • Align category needs to customer experience goals


The category explosion


Ever-evolving customer needs has led to an explosion of categories and assortment sizes across channels and touchpoints. Adopting new operating models; B2B2B or marketplace or D2C and the sudden increase in catalog size is a challenge for anyone who wants to emulate the likes of Amazon. 


Amazon’s success reminds us that the traditional notion of holding a catalog size is outdated. Even shelf space is not relevant in the digital realm. For instance, according to FMI, the average number of items carried in a typical North American supermarket is 31,000 and Amazon thrives on the notion of ‘infinite shelf space,’ that requires an entirely different approach to merchandizing.


What this means for retailers: 


  • There is a constant cry for newness, a need to stay ahead of customer wants and be able to conceptualize, plan and execute category tactics with little or no data on ‘likeness.’


  • There is an opportunity to relook at the traditional construct of set-in-stone merchandize hierarchy with a fresh pair of eyes. Approaches like digital tags and flexible, loosely coupled product relationships can help customers buy solutions rather than SKUs. 


Here are a few scenarios to consider:


Does it make sense to have discrete categories for pasta and seasoning and ketchup, when customers just want to buy ingredients to bring a recipe to life? 


Does a retailer require the flexibility to spin off categories that solve a specific problem – finding the most loyal customer the right outfit for a dinner event rather than letting them navigate through a maze of products and recommendations?


How could the retailer invest in merchandizing tactics on their digital storefronts that help boost, bury, algorithmically validate and garner the right conversions from the first page of search results, despite an infinite shelf?

Key drivers of change in the merchandizing function



The merchant of the future will operate more like a ‘category owner’ and lead a cross-functional team


  • Free up resources to focus on strategic planning

  • Negotiation, planning and assortment will remain core

  • Leverage data and science to drive sales with suppliers

  • Align category needs to customer experience goals



Key enablers

  • Standardized tools

  • Unified approaches

  • Bots for document management

  • Exception driven retailing


Real time, frictionless | High quality data and governance | Automated and agile workflows | Digital visualization

Automating towards better decision making with algorithmic retailing


The art and science of merchandizing needs intelligence and insights to augment human decision making. Decision models and algorithmic intervention bring in consumer insights and demand signals to better tackle the complexity of decision making – using factors such as demand, competition, stock levels, margins, category growth, customer perception of the brand, social influence and more.


A fundamental requirement to algorithmic retailing is process automation. Insights and intelligence-based approaches call for basic levels of automation and streamlined workflows to begin with. Progressively, decisions become faster or even preempted and exception driven. Thus, automation should be tablestakes across the function – from forecasting to assortment, from space planning to pricing and promotions. 


However, we still see many large enterprises with their heavy monolithic solutions, several demand planners, promo planners and pricing analysts operating on macro-based excel sheets to push everyday pricing, forecasting and promo changes to production. For example, there are promo planners who still look at as many as thirty excel sheets with sophisticated black box macros to plan monthly promotions.


Acknowledging rise of ‘category marketer’ persona


Category teams traditionally unearth signals to inform demand, overarching trends and seasonal needs to plan their assortment. And, the retail marketing function has focussed on acquisition, awareness, retention and maturing to spearhead digital marketing operations. Thus, category management and product marketing have developed independent approaches to understanding the customer. 


However, the fuzziness between digital and physical, explosion of social media, rise of influencers and Key Opinion Leaders (KOLs) have led to an overlap of roles and responsibilities. Marketing and category teams have to collaborate to dissect customer personas, their needs, aspirations, demographics, psychographics and social influence. It’s through such a union that they can strategize customer engagement much earlier in the category cycle and feed into assortment decisions. In fact, today's campaigns are designed not just as a vehicle to boost promotions but exclusively to help merchandizers spot trends. 


Here’s an example. Gap teamed up with TikTok to kick off the ‘Gap Hoodie Color Comeback’ competition to crowdsource one of its product choices. The brand’s followers could vote on the logo hoodie’s color slated for a fall release. This approach ensured Gap the much-needed runway and insights for the category teams to plan with precision. This is a classic example of the ‘category marketer’ persona bringing the right mix of category thinking and marketing acumen to help build strategies and tactics that balance customer and category needs.


Expelling awkwardness in supplier relationships 


Vendor experiences are ripe for disruption in brick and click enterprises. Today, traditional suppliers and vendors demand a ‘marketplace seller’-like (enabling) experiences. With the rise of marketplaces and seller enablement tactics, there is significant investment being put into building capability, flexibility and streamlining interactions for sellers. 


Suppliers are also transforming because of exposure to global platforms that provide them with deeper customer insights, joint forecasting capabilities and seamless product onboarding experiences. Suppliers are no longer tolerating outdated tactics of supplier engagement and are demanding new-age experiences, real-time customer insights, enablement and more meaningful partnership.


Interestingly, this problem is amplified  in those enterprises that have transitioned to omnichannel retail marketplaces or are operating B2C and marketplace models in parallel. Walmart has taken a fresh approach to bringing parity (comparable) experiences by dissecting supplier personas into distinct buckets like first-party (1P) suppliers, third-party sellers (3P),  hybrid and service or non-retail partners.  


The classification enables tailored, relevant enablement and digitally meaningful experiences for each of the 1P or 3P personas throughout the collaboration. It further clarifies the value proposition across pricing decisions, listing priorities, listing rules (online only vs. online+stores), available fulfillment options and the customer service support that the partnership provides.


Summing up the tangible benefits of merchandizing transformation



O2O influence Legacy thinking around digital and physical customer personas

Customer omnipresence demands single view across the enterprise and  merchandize value chain


Unbundling of core merchandising functions Rigid and monolithic category organization

Rethinking merchandizing organization as independent core capabilities centered around business domains


The category explosion Fixed catalog size and optimizing for store shelf space

Shelf space and catalog size are outdated concepts 

Optimizing for digital merchandizing and first page listing with more purpose

Customer lifestyle-led retailing Traditional approaches to hierarchy and category structures imposed by monolithic ERPs

Flexible information architecture, tag-based approaches to ride the wave of category explosion and generational customer shifts


Automated merchandizing Manual, excel-based and clunky workflows lacking visibility and accountability

Automated, streamlined and transparent handoffs that clarify true ownership of price, promotions and other category decisions


Large data, algorithm-led retailing

Category level forecasts and plans made in silos based on historical  data and ad hoc research


AI/ML driven planning and execution that is more granular, location-specific and informed by customer behavior
Rise of the ‘category marketer’ persona
Siloed approach to understanding customer demand signals - between category teams and marketing

Merchandizing and marketing collaborate - from curation of assortment to campaigns to subscription based loyalty propositions


Increasing speed and  specificity in planning and execution

Longer, linear planning cycles, rigid seasonal plans with long or no feedback cycles


Faster go-to-market requiring micro planning cycles
Vendor-supplier-seller conundrum

Outdated, manual supplier/vendor management processes not at par with new age seller collaboration expectations


Supplier/ vendor/ seller collaboration and persona relevant digital enablement across omnichannel retail and marketplace models

In conclusion, while digital commerce, stores and logistics have taken the most obvious share of the pie when it comes to retail tech investments, the true leaders are well into their journey of merchandise transformation. The path is hence clear that to win in retail and to win in the increasingly omnichannel retail ecosystem, unbundling this monolithic function is table stakes.


Augmenting the human in the heart of retailing with decision intelligence, bringing speed and specificity to their day to day will bring increased differentiation for retailers. And the time is now to start on this journey of merchandising overhaul!

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