The world isn't like it was last January.
The coronavirus and the response to its spread have reshaped global supply chains (along with a few other things). How are planning departments looking into the future? What's happening on the ground as forecasters scramble to keep supply equal to demand?
He joined us on the most recent episode of The Possibilities Podcast to talk about how planners and forecasters are coping with limited inventory, supply issues, customer service, and razor-thin profit margins all at the same time.
Here are the highlights what we discussed:
The Black Swan
We've spotted a black swan in the last month.
A black swan event is one that you haven't seen before and don't know what it looks like. It takes you by surprise.
That doesn't mean you can't see the shadows of a black swan and prepare for it. But in this case, the coronavirus blindsided everyone. Now, planners have to deal with the current reality and with what is coming even when there are so many unanswered questions lurking around them.
How do you deal with black swan events? How do you deal with this chaos right now? And then once we get through it, how do you prepare for the next one? Because while each black swan might appear unprecedented by itself, these things do occur regularly. There's going to be another black swan in the future. How will you prepare for it?
Why More People Are Moving to Predictive Analytics
All the indicators we build into our models simply help us make better guesses about what will happen. In normal times, companies look at the past and use it as a guide to the future. If we sold X units at this time last year, for example, we will probably sell X+/- units at the same time this year.
It works in ordinary time. Operating your company out of the rearview mirror like that doesn't work during a black swan, though. So people are going more to predictive analytics.
The key component to predictive analytics is more and different data.
Data. That's how we're going to be ready for the next black swan.
So you need the platforms, the structure, and the visibility to collect that data. You need new ways and methods to process that data. You need to turn that data into insights quicker and with less latency. In short, you need machine learning.
How Machine Learning Will Play at the Forefront of Analytics
Machine learning will be one more tool in our planning toolbox.
For one thing, machine learning lets you look at clustering algorithms that may work very well to help segment a business. For instance, you could do traditional ABC type segmentation. Or with machine learning, you could do ABC type segmentation with a viral pandemic thrown on top.
So now you have a Met matrix where you can create some type of machine learning clustering algorithm that will help you segment your business during these times.
There's more that machine learning can do, of course. And its impact on forecasting will certainly continue to grow and will change humans' role in the industry.
How to Improve Your Forecasts
Data will improve your forecasts. The more data you have, the cleaner the data you have, the better you can see things.
The winners during this black swan event will be the ones who have the infrastructure to see across their supply chain and the agility to act on what they see.
The losers will be the ones who don't have visibility, who are grasping at straws because they lack information, and who don't have the agility to act on what they do learn. These demand forecasters are having to do too much "wait and see.:
That's not uncommon. When you're looking at a shock event, most companies take 3-4 months before they react.
On the positive side, a company that can spot a signal, turn that signal into an interpretation, and react to that interpretation can be months ahead of their competitors in a black swan.
If you don’t use iTunes, listen here.