No Easy Fixes
Political instability, global trade disputes and tariff wars are just a few of the threats that the manufacturing industry faces today. According to research group IHS Markit, UK manufacturing contracted for its third straight month in July 2019 – the lowest level since February 2013, wrties José Manuel Benedetti Director of Strategy & Digital Transformation, Insight UK.
In this environment, manufacturers need to use every resource at their disposal to maintain competition. For instance, according to PwC, 81% of industrial manufacturing CEOs said that they plan to rely on operational efficiencies to strengthen growth.
A key resource for manufacturers to exploit is data. Data has been described as the “new oil” for many years, but for manufacturers, its uses go far beyond fuel and lubrication that oil offers. Used in digital innovation projects, data can help manufacturers identify potential efficiencies, challenges and opportunities. It supports the use of technology that increases operational efficiency and agility, and can help manufacturers completely revolutionise their business model, creating new revenue streams, offering them a competitive advantage.
Prediction and Reaction
Used well, data helps manufacturers better understand their market and customers. For instance, by using machine learning to monitor market changes, manufacturers can react to or even predict changes in demand. This helps to increase or decrease production to match or bring new products to market. Similarly, they can monitor customer satisfaction to identify when a product is popular, or when complaints signal a potential production issue. Data used in this way can benefit the business, enabling manufacturers to drive more value through supporting digital innovation and adopting new technologies.
Becoming More Agile with Technology
By using data in combination with technologies such as connected devices, predictive analytics and AI, manufacturers can develop a better understanding of their operations, increasing their agility. For instance, sensors on an assembly line can monitor machine performance and, in combination with machine learning, identify issues affecting performance. Over time, they can predict when maintenance is needed –increasing efficiency and productivity. Similarly, software combined with cameras and other devices on the assembly line can automate quality testing – identifying potential faults in products for further investigation.
From Products to Services
As well as maximising operational efficiency and productivity, many manufacturers are searching for new revenue streams – whether it’s reaching new markets or developing completely new offerings. A current key trend for manufacturers is to evolve themselves into service companies. At its most basic, this means offering additional solutions such as servicing and support. However, some are going even further – for example, by offering a range of products and services as a complete managed service.
As the business completely transforms to a more service-led approach, digital innovation – and data – will be critical for success. The manufacturer will need to remodel its entire customer engagement strategy and how it offers its products, since it will no longer be a tangible product. In addition, when identifying a target market for a service, the manufacturer needs to understand not only the local markets, but how its services will operate in different environments and regions. An engine manufacturer with a one-size-fits-all power-as-a-service offering, for instance, will soon find its costs rise and margins fall in regions where heat, humidity and workload cause engines to fail more often.
Getting it Right
Data might fuel digital innovation and new opportunities for manufacturers, but in order to do so it must be managed and used appropriately. Firstly, manufacturers need to understand their data, and whether it is accurate and unique. Often different business units and functions will have their own data locked away in silos, inaccessible to the rest of the organisation. This means that marketing, sales and production business units may all have multiple copies of the same information, or even contradictory records. Similarly, if data has been recorded by different means over time, there is a real risk that it will be incomplete, inaccurate or inconsistent.
As a result, one of the first steps for any manufacturer seeking to improve its operations should be to ensure it can discover all the data across the entire business. Then, it should audit that data for accuracy, completeness and repetition so that it has a single source of trusted data that the entire organisation can access. It can then begin using that data to identify ways to digitally innovate and transform the business – which should be the responsibility of the whole organisation, not left to IT. This is the additional benefit, in the era of increased awareness of data protection, giving the manufacturer confidence that it knows the exact status of the data it holds.
Like any resource, data alone will not save manufacturers. However, by using it to support innovation and improve operational efficiency, or even open completely new business opportunities, manufacturers can give themselves the potential to succeed.