How robust Demand Planning can contribute significantly to business performance?

Case Studies 

I will share two real life practical scenarios on how demand planning process was improved resulting in improved forecast accuracy, inventory and cost efficiency delivering strong business results  

In first scenario, forecast accuracy was being reported at 0%. On root cause analysis, it was found that it is due to lack of SKU level understanding and sales trends. Actions were taken to improve basic understanding of various product categories, SKU level sales trends and improving accuracy of statistical forecast 

Additionally, forecast accuracy results were analysed and reflected upon every month. Corrective and preventive actions were identified for top 5 highest error SKUs. Over a period of time, these top 5 SKUs forecast accuracy was improved and next top 5 were identified and resolved.  Forecast accuracy improved gradually and within 2 years achieved accuracy levels of 70%. 

Does it look like big achievement or still there can be something bigger than this?  

Now let us look at second scenario, forecast accuracy was 70% and the challenge was can it be improved to 80% levels.  

As forecast accuracy improves, it becomes more challenging to take it beyond 75%, as 75% is considered good accuracy as per industry standard in consumer goods.  

Here additional initiatives were taken, and demand planning process was made effective by discussing SKU level demand plan with sales and marketing leaders and teams. Their relevant inputs were considered which could increase or decrease sale to arrive at real consensus demand plan.  

Biggest magic that these additional initiatives did was that now sales leader was fully committed to demand planning numbers and always striving to try to be as accurate as possible to the demand plan. Some fine tuning was also being done at weekly level to match sales with forecast. Sales leader also had the incentive to achieve the targeted numbers by being closer to demand forecast and it also led to minimum supply constraints. It was a perfect case where sales orders match with forecast and forecast match with supplies with minimum gap between them improving reliability of achieving business targets. 

Second important step was to establish a strong demand plan performance management process where forecast accuracy, bias and top 5 error SKUs were reviewed and acted upon. This was quite similar to first scenario. 

These actions led to transformational improvement in demand planning process and achievement of never heard before forecast accuracy of 93% and forecast bias of 1%. Very high level of forecast accuracy optimized inventories significantly and higher sales were generated at much lower inventories. It also avoided any additional warehouse space requirements and reduced inventory write offs to lowest ever. 

Future Trends and Conclusion  

Future of demand planning will lie in shift from basic forecasting process to create collaborative demand planning process led by senior management. In the new demand planning process, reviews will be led by senior sales, marketing and supply chain leaders.  

AI and advanced technology applications can be used to generate statistical forecast and demand patterns to arrive at base level forecast. Minimum time to be spent on creating data and more time to be spent in reviewing the year-to-date analysis and future forecast patterns with sales and marketing leaders for perfect alignment.   

An effective and efficient demand planning process is a big boon for the organization. High level of forecast accuracy plays pivotal role in ensuring stock supplies as per demand to contribute towards business growth, optimize inventory by lowering safety stock levels and bring cost efficiencies by reduced warehouse space requirements and minimizing stock write offs.  

This is what business stakeholders need to be educated upon to gain the due recognition for demand planning function in the organization. 

It will also be the answer for the question “I will not be surprised if demand planning is not getting due recognition in your organization” which I had raised in the beginning of the article.