The demand planner’s job is a complicated one. A fashion demand planner’s job is intrinsically intertwined with fast moving trends and ever-turbulent supply chains, which makes their role of forecasting customer demand and maintaining inventory levels in the most cost-effective way not an easy one. Poor demand planning is costly – from product shortages and empty shelves, shipping delays and unhappy customers, to excess inventory which require expensive clearance discounts, stock wastage and drop in profit margins, the implications for the business can be dire.

The complexity does not end there. Like any job, demand planning has its specific challenges. Most of these challenges center on data access and visibility, as demand planners rely heavily on data for their forecasts. The impact of macroeconomic events on supply chains and production present another set of difficulties. And finally, streamlining demand planning requires the collaboration of many teams. When this does not happen as intended, it will be difficult to implement demand plans. In this blog, we discuss these challenges in detail and explore how digital technologies can help demand planners navigate these roadblocks.

Top 3 challenges facing fashion demand planners

1.Data silos, lack of a unified data view and formatting problems

Demand planners liaise with many teams within an organization to understand the market outlook and sales performance of many channels (such as online, in-store, third party retailers). They need access to real-time data as well as historical information. Without the right tech for demand planning or business intelligence, this data collection is a tough task. Demand planners must collate all these data sets, often in spreadsheets, while relying on other departments for accurate and timely data. Delays in data collation, as well as the fact that the data collected from these many sources often exists in silos, makes it difficult for demand planners to access a unified view of data for their forecasting.

In addition, these data sets are typically presented in the spreadsheets in multiple formats. The demand planner hence spends a significant amount of time formatting and organizing data for consistency. As this is a manual process, not only is it time-consuming but it also increases the probability of human errors, inaccuracies, and misinterpretations.

2. Supply chain constraints and fluctuating demand

The past two years alone have highlighted supply chain vulnerabilities more than any other time in recent history. Lockdowns in key manufacturing locations, temporary factory closures, reduction in production activity, sourcing problems, and transportation delays have all affected supply chains. Warehouse capacities are under strain too. Demand planners face enough difficulties when global events impact supply chains during more stable circumstances. In today’s volatile political and economic environment, there is even more uncertainty. Sometimes, only the relevant purchasing or product teams may have knowledge of manufacturing delays or factory closures. A demand planner’s entire forecast and plan will need to change according to ever evolving developments.

Following the easing of lockdowns and other COVID-19 restrictions, fashion retailers have re-opened stores in certain regions and there is a consumer shift from online back to bricks and mortar stores. These developments mean that demand planners must now reassess their omnichannel forecasts and understand the new demand patterns that will emerge as consumer behavior shifts in the post-COVID world.

3. Cross-functional collaboration

Once a demand planner collects and deciphers data, creates a forecast, and gains approval from their management, the next step is to find consensus with the many teams that play a role in the demand planning process. Not everyone will agree with the plan as each team could have a different understanding of what works best. They may not even consult the forecast. There will be accountability issues too – if teams act in isolation, someone must be responsible for failing to execute the original forecast and any insufficient or excessive inventory. It is crucial that all departments are on the same page to perform the difficult task of balancing forecasting and inventory levels.

Eliminating the guesswork in fashion retail with technology

Demand planners have the arduous task of ensuring that the right product is in the right place, at the right time, at the right price, and in the right quantity. Technology will be a key enabler for better product demand prediction, helping fashion brands and retailers avoid the death knell of over- and under-stocking

The devil is in the details – retail planning technologies for the new normal

Most retailers still demand plan using a combination of manual, paper-based, and spreadsheet approaches that often draw from siloed data sources. This leaves retailers over-reliant on historical data that does not truly reflect the drastic shift in consumption patterns and prevents them from swiftly responding to changing market conditions. Businesses still struggle to estimate the impact of external stimuli on their supply chain in a dynamic fashion, and this was quite apparent right through the pandemic and even after COVID restrictions lifted. This year, retailers have resorted to Black Friday markdowns much earlier in the season, and in a far more aggressive manner, to get rid of the excess inventory that is  bound to clog up warehouses into Christmas and beyond. It’s clear that traditional demand forecasting and planning methods and tools are simply not able to handle the complexity and data-intensive nature of today’s omni-channel fashion retailers.

A modern approach to demand planning and forecasting must be able to handle the increasingly integrated, multi-channel nature of today’s retail business, as well as variable impacts like COVID-19 and demand fluctuations resulting from supply chain delays, inflation, and high interest rates.

Modern retail planning systems have a host of tools designed specifically for fashion retail. From Weekly Sales, Stock and Intake (WSSIs) to Merchandise Financial Plans, and Store Plans to Assortment Plans, Retail Planning tools provide the functionality required by planners in applications that have been prebuilt in line with industry best practices. While some have a spreadsheet look and feel, others are much sleeker.

Such systems are updated, sometimes in real-time, with product orders, warehouse operations, inventory levels, etc. This means that demand planners are better prepared to respond to the impact of supply chain disruptions and plan accordingly.

ERP: A remedy for retail’s data quality woes

Quality insights from a Retail Planning system are dependent on decent quality data.  Garbage in, garbage out, as the old computing phrase goes. So, how do you ensure decent quality data? The answer is a solid system of record, such as an ERP.

An ERP that’s built for the fashion industry will not only help streamline the entire operation, from fibre to finished product. An ERP can also track the inventory in a precise manner, enabling demand planners to align and manage inventory, while also helping with production capacity and planning, accurate order fulfilment and much more. As the state of inventory is captured throughout the entire supply chain, this data can be fed into edge products, such as retail planning and business intelligence solutions, allowing demand planners to make better decisions, faster. An ERP helps build a strong data pipeline by recording relevant internal data such as sales data by channel and location, out-of-stock rates, inventory turnover, lead times, production times, obsolete inventory and other key inventory metrics. In the absence of an ERP, disparate systems running throughout the apparel manufacturing process will mean that the organisation does not have access to up-to-date information.

Another benefit of an ERP is that they can be integrated to your Retail Planning system to automatically drive procurement once the demand plan is approved.

Business Intelligence to lead with intelligence

ERPs are brilliant at capturing data, but they aren’t the right system for processing, analysing or visualising data in meaningful ways. This is where a Business Intelligence solution comes in. If you have one of those handy, and you really should, then the best solution is to integrate your Retail Planning Solution to your BI solution. Here’s why.

Sitting on mountains of raw data is unlikely to do much for fashion retailers if they are unable to interpret and act on these insights. While moving away from legacy systems and spreadsheets is part of the solution, retailers must establish a single source of truth so they can be proactive, instead of only being reactive to market changes. A Business Intelligence system provides a consistent, single source of truth across the entire enterprise. It does so by building a strong data pipeline that incorporates multiple sources of data including your own data from all departments via the ERP, vendor data, manufacturer’s data and even Big Data from social media. They extract, translate and organise this data converting all those 0’s and 1’s into golden nuggets of useful insights.

Reports, graphs and other visual aids are available to all stakeholders, to slice and dice as they require. The single source of truth extends way beyond demand planning to all areas of the business. This way the data used by the demand planners is the same as that of a strategic management summary, giving clarity and visibility. Analytics, machine learning and AI could even help interpret the data, discerning trends and outliers that could easily be missed. Trigger alerts can be setup along the workflow, so that all affected departments, planners included, can be alerted when things are not progressing as they should. Demand planners must also go beyond a siloed approach and consider other relevant information from other departments such as campaigns, promotions and price changes from the marketing department, POS data from the stores, and new launches and product discontinuation information from product teams. This internal data must then be enhanced and contextualized with external data signals such as consumer purchasing habits, economic conditions, social media data, weather predictions, and more. The BI system can collect all these pieces together and then feed it into the Retail Planning system to facilitate smart, sophisticated planning.

This drive to digitize the fashion supply chain must be informed by a potent cocktail of systems, including but not limited to an ERP that caters to the specific needs of the fashion industry, retail planning systems and a business intelligence solution. Visibility into data and real-time inventory information forms the base of this digital cocktail.

Fortude has extensive experience working in the fashion retail industry, providing businesses with the solutions that help them streamline their business operations, manage their processes end-to-end, and gain access to data and analytics capabilities. Find out how we can help: https://fortude.co/industry/infor-fashion-erp/.