In recent years, you will have been continuously bombarded about robotics, artificial intelligene (AI), blockchain and machine learning. Now these are not just buzzwords but real innovations that will help your supply chain move forward. However, the question is: how do you bridge the gap between your current supply chain solutions and truly AI-focused work?
Despite all the wonderful vistas, research firm Gartner revealed in one of its latest reports that at least 80 per cent of organisations will continue to rely on spreadsheets for the time being. The reason is that for many organisations, AI is still a magic word. Even if AI were mature enough for large-scale implementation in the supply chain, thousands of smaller companies would still not have the capital to invest in these solutions.
Beyond the hype
But affordability is not the only barrier. You cannot make good use of advanced solutions until you solve more fundamental problems with the way your organisation processes data. The hype around AI has had the unfortunate effect of prioritising more pressing problems that can be addressed with simple, affordable software solutions.
Supply chain departments do take on more and more challenging IT projects, such as omni-channel initiatives. However, due to changing circumstances, many IT departments are proving unable to keep up with tomorrow's challenges. This is caused by an overly formal way of working in many IT departments, which does not allow them to keep up with the dynamics of the market, for which they are becoming increasingly responsible.
Data reliability
First, addressing your organisation's instant data reliability and digital access is the best way to solve today's challenges
If you have not already done so, addressing problems caused by low reliability data and data silos between departments should be your first priority. Solid supply chain operations rely on high-quality, reliable data flowing freely between departments. Normalising data and bridging silos between departments are not sexy problems to solve, but if you leave it, you will fall hopelessly behind and will not be able to make the step forward.
Data Science
Not surprisingly, data scientists and specialists spend as much as 80 per cent of their time preparing data. Where you might expect them to focus on designing and building models.
The fact is that models are only as good as the data and formats used. This is because it costs a lot of money to catch all the anomalies and exceptions within the models. That takes a lot of coding time. So for that reason, it becomes understandable that people are mainly concerned with 'manipulating' the data.
To successfully meet your supply chain challenges, you need an organisation that has a transparent structure and clear shared objectives. Too often, organisations lose themselves in a flight to the front under pressure of cost cutting, which ends up disappointing or even endangering the organisation.
You can avoid these pitfalls by starting with a clear business plan and objectives. What results do you expect? Who and what should generate what revenue and who has what responsibilities? Take the time to get informed about the possible AI solutions that would be applicable to your organisation. One thing is certain: the spreadsheet has had its day as the basis for your business decisions.
Author: Hans Groen - Advisor Supply Chain and Performance Management
