During the pandemic, much of the focus on the supply chain has tended to be on the supply side, and rightfully so, given the advertising of sourcing, production, distribution, and transportation issues. As a result, organizations continue to search for increased productivity, flexibility, and agility through software such as Lean, increased automation, robotics, and artificial intelligence, among others.
However, the supply side should not be the only area of focus. To one degree or another, human behavior has tended to exacerbate the problem, resulting in fluctuations on the demand side.
The effect of panic buying, hoarding, and changes in last-mile delivery option have created a clear example of the whip effect, where differences at the consumer demand end of the supply chain create a multiplier effect that accentuates and amplifies weaknesses in upstream operations.
Improve timing and accuracy
This brings us back to visibility, collaboration, and communication as keys to improving order timeliness and accuracy. These strategies can help reduce the impact of a global pandemic or other local and global events that appear to occur regularly.
Companies that still rely primarily on using historical demand data to create forecasts are, in effect, driving while looking in the rearview mirror. We know the result.
Not only do we need to cooperate with our main customers, it is also necessary to go deeper towards the customer. Using data such as retail points of sale, e-commerce (POS) and withdrawals from customer warehouses helps determine what is really happening.
It also helps to monitor events such as weather, environmental issues, changing tastes and preferences (sometimes triggered and found in social media) that can cause fluctuations in demand and assess their potential impacts.
Fortunately, we are at a time when we finally have a better set of technological tools to deal with the increasing amount – and speed – of new events and changing tastes and preferences that can increase the volatility of demand,
Today, organizations need to develop very robust demand sensing and shaping processes with the help of technology to better smooth out and predict this volatility, at least to some extent. Organizations then also need to share these resultant, more accurate forecasts up and down the extended supply chain to maximize benefit or “surplus” for all participants.
Enable accurate predictions
However, as the volume of data coming to us is increasing exponentially, it is time to finally start adopting the following concepts to enable more accurate predictions through better and more informed decision making:
Supply chain data analytics. This consists of:
- Metadata (what happened)
- Diagnostic analyzes (why it happened)
- Predictive analytics (what could happen)
- Meta analytics (what action to take)
Machine learning, which is based on the idea that machines must be able to learn and adapt through experience.
Artificial intelligence. Artificial intelligence is the general idea that machines can perform tasks “intelligently”. AI applies machine learning, deep learning, and other techniques to solve actual problems.
Improving ordering processes requires not only the use of new and better technologies, but also employees who are trained, willing and ready to use them.