Talk of Artificial Intelligence (AI) in manufacturing has been around for years. But before the pandemic, the industry had started trialling and deploying new solutions at a fairly slow, careful pace. That has now changed. AI is no longer seen as a ‘nice to have’ and has become business-critical. Supporting this, a recent BCG report highlighted that “AI will be a must in the post-Covid world”.
It’s now time for businesses to seriously assess the role AI can play in manufacturing; to understand how it is already helping, where it will deliver added value in the new normal and what cultural and organisational changes will be needed to make deployments a success.
Manufacturing businesses with AI technology at their core are able to improve customer service and optimise operational processes. For workers, it will allow them to focus on more value-adding activities by taking away repetitive tedious tasks, improving business profitability at the same time.
Agility to navigate change
The pandemic has impacted businesses in many ways, but particularly around supply chain and demand. It has forced businesses with complex supply chains to realise the importance of agility. Traditionally, supply chain managers prefer to operate lean operations which minimise redundancy in favour of cost reduction. However the fact of the matter is, uncertainty requires redundancy, which increases costs. It can be expensive to build in the suppliers who can help you be more agile, and duplicate supply chains so you can still get the materials and parts you need should disruption occur. However, AI can offset this cost; manufacturers can optimise pricing through predictive maintenance and better planning.
Coronavirus also tipped consumer demand on its head. At the time of the global outbreak, luxury items such as Easter Eggs were left clogging up the shelves while essential goods such as flour and cleaning products were snapped up. As such, traditional purchasing patterns were disrupted which has a huge financial impact on businesses. In this period of uncertainty, supply chain professionals need all the help they can get to address demand. Because AI and Machine Learning (ML) applications can analyse large amounts of data from different sources much faster than humans, they can uncover emerging trends in consumer preferences. This enables faster decision making which is critical during this time of uncertainty.
Even before the pandemic, a recent report from CapGemini revealed that Danone uses machine learning to predict demand variability and planning. The technology improved its forecasting process and led to more efficient planning between different functions, such as marketing and sales. It has led to a 20% reduction in forecast error and a 30% reduction in lost sales.
Should we face a second peak of this pandemic, getting AI in place now will help essential businesses adapt more quickly.
The challenges to watch out for
Whilst the benefits are clear, adopting AI in business-critical areas can be daunting. Many businesses have failed to realise the benefits of AI due to roadblocks within the organisation. A recent report from MIT Sloan found seven out of 10 companies report minimal or no impact from AI so far. For example, among the 90% of companies in MIT’s study which invested in AI, fewer than two out of five reported business gains from AI in the past three years.
A lot of these issues often come down to a lack of understanding what adoption of AI means. Other leaders feel pressured to adopt AI before they plan how it can best support their business. There needs to be thought given to the amount of effort and time that is required to invest in the solution, and to what happens if something goes wrong. To plan successfully, organisations must also have the necessary executive support. The projects that derive the most value for their companies are those that see AI as a core part of their overall business strategy. The full, informed and active support of the CEO and other senior executives is essential.
Implementing AI isn’t a quick fix or add on. The senior team must be willing to embrace an organisational shift to get full value from this technology. Trying to enhance pre-existing processes and legacy structures with AI is a mistake. To build an AI-focused operation, you need to redesign legacy processes, technology, and structures. This is why ERP systems are a great place to start, as they are a foundational building block for business processes.
AI and ERP
In the past, ERP systems were used mainly for administrative functions, like reporting and data management. Now, with intelligent technologies like AI and ML, ERP can play a much more important role in improving business processes.
Intelligent ERP systems, embedded with AI can identify trends and make predictions, recommend actions, and process complex data for manufacturing and supply chain organisations. AI can enable the system to self-correct in real-time, allowing operations to run more smoothly and saving employee time and effort. Intelligent ERP frees employees to do more meaningful work, allowing them to generate more value. As AI constantly becomes a more accessible resource, it allows businesses to work smarter, make more accurate decisions, and forecast more effectively.
AI and ML will reshape a lot of business activity and will bring choices for companies to decide how to use it. AI comes with opportunities, and also risks. Up-skilling and cross-skilling of staff will need to be addressed. Leaders should look to AI to operate more efficiently or increase productivity, rather than as a cost-cutting exercise. Above all, to realise the full benefits, the entire organisation needs to embrace change.