Demand forecasting helps you avoid stockouts and overstocks and lets you hit the sweet spot in-between. If done properly, it also lets you align your production schedule with your sales cycle resulting in huge cost efficiencies.
So why aren’t more companies doing it right? Well the truth is, more and more are, it’s just a case of using the right blend of technology and data.
The technology we have access to in both our professional and day-to-day lives is getting better and better at making predictions. Whether it’s Amazon telling you about a new book you’ll absolutely love, or your Transport Management System warning you to expect late shipments due to traffic, technology is getting more and more accurate.
Artificial Intelligence (AI) is not new. It’s been around for decades and we are only just beginning to scratch the surface of its potential. Breakthroughs in computing power and efficiency have boosted machine learning capabilities and solutions are now able to analyze huge data-sets and relay insights and opportunities in real-time.
This continuous process, which can even consider changes in the learning model, is called ‘deep learning’ and reflects the real-time analysis functionality of these systems, which are able to continuously absorb data and update how it is interpreted.
So how does this apply to forecasting? I’m glad you asked!
Using AI to drive your forecasting has several advantages. Firstly, whereas traditional methods only consider linear factors such as seasonality, AI is able to go deeper and pull in more data to reach more accurate conclusions. AI can leverage Big Data and analyze any number of causal factors that might impact forecasting. For example, real-time weather conditions, holidays, fuel prices, traffic and much more.
As a result, AI can provide you with new insights meaning you can potentially streamline tasks and become more efficient, resulting in faster processes and cost savings.
Now, before you get ahead of yourself and hand over control of your business to a smart phone, remember that forecasting is only as accurate as the data that you feed in. Providing the most advanced systems on the globe with false data will give you false results. So when it comes to tendering, having all of your historical data to hand is a massive advantage.
TenderEasy can help you there!
Finally, to enjoy the full value of using of AI in demand planning, you need to understand that AI empowers and enables people. It doesn’t replace them. People implement change, build relationships and understand issues that are currently beyond machines.
So there you have it. Man and machine working hand in hand to predict the future – it’s already happening!