Five Signs that Traditional Demand Planning Tools are Failing You
Demand planning has always been difficult, but it may never be more challenging than it is right now. We are seeing widespread challenges in numerous industries. While the last year of COVID-19 has made things more difficult, every company we work with quickly points out that these challenges are not new.
A painful realization
That said, it’s abundantly evident that traditional approaches to demand planning and sales and operations planning (S&OP) have broken down during the uncertainty and volatility of the pandemic.
Five tell-tale signs of failure are:
- Struggles with demand forecast error
- Underperforming (possibly even turned off) baseline statistical models
- Unclear if S&OP process improves accuracy
- A less than analytical approach to evaluating inputs
- No clear guidance to improvements (you are on your own to figure things out)
Challenge your vendor on these three capabilities
No one has a perfect crystal ball, but your forecasts should still be good enough to drive short-term and longer-term decisions. It’s time to take your vendor to task and demand more. To this end, here are three areas where you should test your vendor’s capabilities:
- Erratic demand: We’ve found that most fast-moving consumer goods companies (FMCGs) have 40-80% of volume with erratic demand patterns. Traditional statistical and simple AI approaches cannot cope with this and have produced incredibly high levels of error. Noodle.ai has developed powerful proprietary engines that address these challenges.
- ‘Meh’trics: Many companies measure lag 2-month or lag 3-month demand accuracy and have seen performance decline dramatically. Unfortunately, the situation is even worse because weekly accuracy is critical for inventory deployment and urgent production change needs. We find that companies do modestly better on the horizon that they report metrics for but dramatically worse on others. Noodle.ai’s models optimize across many time lags and produce stable performance where other tools have a wide range of error levels.
- Wild goose chases: We have heard many stories of other vendors asking for infinite data sets only to find that most are not predictive. Noodle.ai has a deep understanding of what data sets are typically predictive and get those configured quickly. Your teams are already maxed out and do not need to go on data wild goose chases.
Challenging your vendor on the above will reveal inherent weaknesses in their approaches and help you decide if you have purchased the right demand planning solution. It may be time for an alternative. Noodle.ai is happy to help you transition off those antiquated solutions and discover the power of AI-enabled demand planning and forecasting.
What’s next? The Demand Signal AI Predictive Pilot
Accelerate your planning decisions, increase forecast accuracy, and improve your productivity with a 3-month pilot implementation, with the option to go live in month 4. Click here to download.
At Noodle.ai, we’re bringing the old concept of the supply chain into the 21st century, melding it with manufacturing and distribution into a seamless materials-to-shelf flow.
- Deep Probabilistic Decision Learning Returns Perfect Flow to Operations
- Perfect Flow: Augmented Intelligence and the Elimination of Manufacturing Waste
- AWS Partner Network Blog: How CPGs Can Improve On-Time, In-Full (OTIF) Deliveries
- The Future of Quality Management in Modern Manufacturing: AI-Driven
- How AI Can Solve Manufacturing’s Waste Problem