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Given the fast-paced nature of the retail industry, Merchandise Planning has always been intense, with teams battling to keep to tight schedules whilst making critical decisions at a moment’s notice. With speed and intensity accelerating, retailers need to prioritize their Merchandise Planning processes and maximize their efficiency so that teams can not only make better-informed, impactful decisions based on key data but also spend more time on other value-adding activities. Here are 3 approaches to process improvement that we suggest.
Plan at the optimal hierarchical level
With time constraints, many Merch Planning teams resort to a blanket approach when creating a plan. It might be quicker to analyze data at a high level but increasingly, deeper analysis is required to ensure that the planning decisions are correct the first time around. Businesses need to devote time to ensure that planning is completed at the optimal hierarchical level. This will allow teams to have better visibility to identify areas of opportunity as well as areas of risk in terms of sales as well as stock levels.
It also helps with data organization – a well-built category hierarchy, for example, can provide the correct structure and logical product flow. This helps customers to navigate websites more easily as online categories will be defined by this same hierarchical structure. A good hierarchical structure also enables better integration with supply chain partners, and the coordination between retail planning and production also improves which reduces production costs and inventory requirements. With higher quality data better organized, businesses can draw crucial insights to support merchandising decisions.
Automate tasks
All too often, Merchandising teams do not have enough time to focus on crucial activities. However, it is now increasingly possible to automate many routine tasks that take up a lot of time. Using advanced planning predictive analytics systems is a great example of this: these technologies can automate historical analysis and can create predictive scenarios which guide teams to make quicker, data-informed decisions. These systems also have the ability to amend plans to account for scenario changes which eliminates the need to spend countless hours re-forecasting plans again and again. For instance, during the pandemic, Amazon used AI-driven predictive forecasting to respond quickly to changes in the demand for toilet rolls when sales surged.
Without advanced planning systems, making changes to the plan can be a tedious task. Teams that rely on manual data entry will need to be wary of making errors, accidentally overwriting files, and how they organize all their data as a whole. Planning automation tools will automatically re-calibrate the plan and intelligently adjust “sub-plans” to make sure all numbers make sense across all levels of the business, saving teams hours each week. Additionally, dynamic services with web-scraping and predictive impact analytics can even automate pricing and promotions.
Invest in Data Science
Many rely on gut instinct and their own analysis and research when making decisions, however, we aren’t intellectually capable of processing such large data sets like a machine can. An effective approach to decision-making combines human instinct and data science but many Merchandising functions don’t have the relevant skills to effectively utilize data science capabilities. Companies need to invest time and money into upskilling their employees so that they develop cutting-edge data skills that they can continue to use to optimize merchandising decisions. This ensures that decision-making is not only more effective but also a far more efficient process that frees up time for other work tasks.
Businesses with a data science team should consider the interactions between the data scientists and the Merch Planning teams. With data playing a more crucial role than ever, data science and merchandising functions should be working regularly together to ensure that decisions are being made as effectively as possible. It’s important to note that data science isn’t replacing human decision-making, it is supporting and enhancing those decisions.
Retailers need to automate tasks, invest in data science, and ensure that planning is completed at the optimal hierarchical level to not only improve merchandising decision making but also free up time for the Merchandising teams to spend on more critical work tasks. At TPC, most of our consulting team have a background in Merchandising and, by drawing from their own experiences, successfully support client Merch Planning teams worldwide with the selection and implementation of data science tools and other effective methods that streamline business processes.
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