Predictive analytics for cost forecasting is the process of using the cost model to estimate future costs. If you are a small or medium sized company, especially in the manufacturing sector, you already know the value of cost modeling and cost forecasting. To reiterate, cost modeling is an exercise by which you systematically relate the price of your input factors (raw materials, labor, transportation) to the cost of producing the manufactured part.
But if you are doing these activities the “traditional” way, then you also know what some of the challenges are. The work is cumbersome, especially if the products manufactured are complex. The cost estimates developed tend to be highly dependent upon experience and “gut-feel”. In other words, somewhat subjective.
Predictive analytics for cost forecasting helps you overcome both of these challenges. We recently showcased the experience of one mid sized automotive supplier who uses analytics for their cost forecasting. In their experience, using predictive analytics to develop the cost models has led to a 12 fold decrease in the amount of effort required to develop cost forecasts. They manufacture dozens of products. Each product cost depends upon 40 or more inputs. That is to say, the amount of productivity efficiency gained by using predictive analytics is substantial.
On top of this gain, the models developed are mathematical rigorous and leave no room for subjective interpretations. Thus to summarize, using predictive analytics for cost forecasting results in the following two clear benefits:
- Significant reduction in the effort required to build cost models
- Significant reduction or complete elimination of subjectivity in making forecast
Originally posted on Tue, Nov 29, 2011 @ 09:06 AM