The merchandise Planning at its core is to ensure that right merchandise is available at the right time in right quantity in right size at the right point of sale for the customers.
One of the biggest bets a retail organization makes is to buy merchandise and placing it in stores. The buying decision implies supply chain cost, warehouse cost, operating expense of a store etc. which can easily multiply if a wrong decision is made.
Merchandise Planning provides a framework for quantifying (what & how much) buy and sell of merchandise depending on historical data, current market trends and expectation of both internal & external customers. This helps in satisfying customers and achieving the set financial goals by minimizing inventory overflows.
Merchandise planning processes are cyclic in nature typically driven by buying seasons
Before the season is launched, the plan provides the guidelines for co-dependent teams the direction of strategy:
Setting of the financial targets for a season/fiscal year. This sets the financial goal like revenue, gross margin, to be achieved from the combination of products and stores and other sales channels.
The plan needs to balance overstocking the warehouse with old/unsellable merchandise or understocking new inventory which may lead to loss of sales and not meeting the financial targets.
A Detailed plan at product level reflecting quantity bought for each product to allocate to different stores and channels so that the demand of customers is met and business can achieve profitability.
After the season is launched, this process helps in monitoring the performance and take corrective actions to achieve targets.
Once the orders are sent to manufacturing units, it is important to track its inwards as per expected timeline. Based on the weekly inputs before and during season launch, business owners can take actions against delayed inwards, quality issues, cancellation of styles etc.
The weekly analysis considers what is selling, where is it selling and how much more stock is available for sales. Based on this, business owners work with supply management teams for the movement of stocks from one location to another based on sales trends.
Although the merchandise is bought based on demand, trends and seasonality, not all merchandise gets good response. To avoid adding on to the inventory liabilities, decision of markdowns or sale offers is decided by business owners to improve sales on specific product lines.
All the stakeholders review the performance against the pre-season planning for the various Key Performance Indicators (KPI) set as targets. This includes multiple reports and dashboards to map reality vs expectations.
Towards the end of one planning cycle, the analysis of inventory takes priority. Decisions need to be made whether to liquidate as much inventory as possible by lowering margin or carry inventory to next season.
The end of season leads to a reconciliation of inventory and a financial analysis. However, the most important aspect is to draw on lessons learnt from the previous season so as to plan the next season better.
Most of the organizations still use spreadsheets to make plans. These spread sheets are not sufficient to provide business the details required to make accurate decisions. Planning teams are often lost in maintaining multiple files with formulas that makes processing of multiple spreadsheets a challenge.
All the files are required to be created by individual stakeholder season on season. The intricate process takes up a lot of time where huge data is collected from multiple sources and put into formats for stakeholders to understand. This may also lead to human errors which can cause organizations dearly in the long run.
Each individual can give different type of solutions for a given problem. Manual processes allow each team to have different ways of working, leading to inconsistencies at a global level. The inconsistency to present accurate data may lead to disorientation and risk of taking wrong or delayed decision making.
More time is spent on gathering, preparing data to create plans rather than analyzing and executing a plan. With huge chunk of data flowing in from different sources per second basis the traditional ways of working sometimes lead to a lag in execution due to loss of time in understanding the data and acting upon it.