In the world of automotive sales, brand loyalty, advertising, and incentives drive a majority of purchasing behavior by consumers. But so does stock – is the brand and model available with all of the accessories a buyer wants when they want it? This is the classic problem in automotive production – accurately predicting demand by model and variations on model. Automotive companies have long sought to synchronize their production output with consumer demand.
Automotive production relies on the company’s ability to accurately forecast demand which guides every decision, from the sourcing of raw materials through production to customer delivery. The classic and now obsolete method of forecasting uses historical data and projections to create the demand plan and forecast and relies on existing model configurations to produce stock.
This method has shattered under the pressure of consumer expectations. Worldwide, the auto industry faces fierce competition and demand is notoriously difficult to accurately predict. Consumer sentiment swings quickly, trends emerge and fizzle, and local economic influences are substantial between states, territories, and countries. Manufacturers also face pressure for price reductions, faster delivery times, quality improvements, more environmentally friendly models, shorter product lifecycles, reduced product development costs, and shorter time-to-market.
These pressures driven by consumers and regulators make it particularly difficult to forecast sales and plan demand accurately across the entire supply chain. The lean manufacturing principles and just-in-time (JIT) inventory control which helped companies like Toyota succeed are no longer sufficient. Many manufacturers still plan production based on a forecast that is really nothing more than a best guess as to what models will be in demand by consumers in which city and country. Unfortunately, this results in stockouts and unsold inventory and can create a bullwhip effect – larger and larger swings in inventory in response to changes in consumer demand. Manufacturers end up holding too many of the wrong models and running short on what customers actually want.
The modern demand driven forecast connects directly to customer satisfaction. The customer’s experience is critical to the brand’s success and brands that deliver strong customer experiences tend to see higher revenue growth. This makes accurate demand planning all the more critical – a great customer experience (matching them with the car or truck they want at the right time) creates a positive brand experience which impacts the bottom line over the long term. An inaccurate forecast results in stock that’s impossible to move, languishing on dealer lots to be sold off later at a loss.
This is the problem that India’s largest auto maker had. Their forecasts were full of errors, leading to lost sales, stockouts, dead inventory, and late deliveries. This created a drag on production and on customer experience.
The company’s goal was to improve their conversion ratio and understand which of their prospects they could target to find opportunities for cross sells and upsells.
CT Global Solutions built a software solution based on SAS® Demand-Driven Planning & Optimization (DDPO): Forecast Analyst Workbench (FAW), and CFW (cannot find a product these initials relate to – please provide)
One of the essential elements of a successful demand-driven approach is having the right demand flow technology in place with customer demand as the primary signal that guides production.The company can now accurately forecast vehicle demand at a city level. Production plans are now better aligned to market demand and the result is fewer lost sales and improved customer satisfaction due to timely deliveries.
The SAS demand planning and forecasting solution improved the company’s bottom line by reducing lost sales, reducing dead inventories and improving delivery time, which improved JD Power auto rankings that further influenced sales.
Auto manufacturers who succeed apply new technologies and sophisticated analytics to their demand and forecasting models to make their forecasts more responsive to customer demand. While globalization has created lots of opportunities for automakers, it has also created pressures to improve styling, enhance quality, increase efficiency, and create innovative models to attract customers in existing and new markets.