Leading Indicator Forecasting Engine
Anticipating on business turning points
It's time to bring the outside in.
Enter the digital era and include data-driven macro-economic & market dynamics in your decision-making.
Integrating internal and external data with predictive analytics will help you to better anticipate turning points in your sales or in your market.
Quantifying the specific impact of market turbulence on your company’s top and bottom line helps to steer your company through rough waters.
Having better visibility gives you a strong competitive advantage in your market.
A common forecasting process consists of a statistical baseline combined with a collaborative process to add customer-specific information. Unfortunately, there are strong limitations to this common approach as it fails to predict sudden business turning points.
Bringing the outside in by integrating leading external data in your planning processes acts as a canary in the coal mine for business turning points.
Winning the forecasting game is about integrating ALL possible sources of information: Statistical, collaborative, and external data.
Our 4-step approach is designed to guide you through the broad landscape of external data. These steps will enable you to identify relevant indicators from external data and combine indicators in a forecast model that acts as an early warning signal for business turning points months ahead.
STEP 1: Indicators
Gathering different sources of external information to identify potential demand drivers, relevant to your business. Sales, marketing, procurement, and customers might all have relevant insights.
STEP 2: Matching
Identify which data makes sense statistically and business-wise. The goal is to find the balance between indicators with a strong mathematical match, and the business understanding of the indicator.
STEP 3: Forecast
The model uses machine learning techniques to select relevant indicators and decides which leading value to use. It can take some iterations to validate the model with your business.
STEP 4: What If
Monitoring the identified indicators closely and monitoring deviations between forecasts (statistical, sales & leading indicators) will give you early warning signals in case of upcoming turbulence.
Just do it
That's what Christian Backaert, Global Supply Chain Excellence Manager at Solvay, has as advice for you while sharing his experiences of integrating external data into the demand planning process at Solvay.
"The leading indicators & leading indicator forecast has become part of our regular review to better understand the market and go from reactive to proactive management."
"Most important has been to see the general trend and turning points in the sales and compare with the expected annual growth expectations."
Head of Marketing
"The most important question of demand reviews becomes, do we know why the sales rep forecast is different?"
Global S&OP Lead
"We learned that the inventory in the pipeline is more important than end-market sales. The strategy within automotive supply chains has changed from JIT to maintaining safety stocks."
Your top 3 recommendations from our Data Scientist, Gylian Verstraete
Would you like to get a better grip on your demand drivers? Let's have a chat and I'll give you my advice to start acting tomorrow.