Oliver Wight EAME: the benefits of data in manufacturing
What are the benefits of data in manufacturing?
In today’s digitally dominated marketplace, data is an essential commodity because of its infinite potential to inform and improve the way that organisations serve their customers. Accurate real time data can be used to create a complete picture of demand, based on the current realities of consumer behaviour. This allows manufacturers to respond to real-world events, market shifts and changing buying trends on a daily or even hourly basis, creating an ever-improving customer experience.
What are the challenges of data in manufacturing?
Nowadays, the information available on consumer behaviour is vast and changing minute-by-minute. The key to utilising the data effectively is managing, assimilating and interpreting the volume and frequency of inbound data using analytics and the latest mathematical algorithms to turn it into valuable information.
What are the current trends within manufacturing when it comes to data?
Peer reviews and testimonials have always had a massive influence on consumer behaviour, but the speed and reach of these have been ramped up by online reviews. Social media has been a game-changer, affecting customer behaviour in ways that have left some organisations struggling to play catch up. We are currently in an age of ‘influencer’ marketing, where a prominent social media personality can be the make or break of a product – causing huge surges (or dips) in demand which manufacturers need to be ready to deal with.
What is the best strategy for driving the best business value from data?
Remember that one size doesn’t fit all. Top performing companies use data to identify different customer needs and segment their markets, with different value disciplines assigned to each one. The real-time data received for each of the different types of consumer provides the information required to align their supply chain strategies, plans and products for each market segment accordingly.
What are the benefits of data analytics for manufacturing?
In the face of increasing consumer demands, an already competitive market has become increasingly cut-throat, so to gain an edge over the competition businesses must not only meet customer demand, but predict it. Data analytics allows organisations to quickly, efficiently and effectively translate thousands of data points collected on consumers into deep insights that allow them to get to know their customers better than they know themselves and create an integrated and personalised customer experience.
What are the challenges of data analytics for manufacturing?
Data can provide valuable information that leads to knowledge, but this is only useful if the data is accurate. In many businesses a lot of high-level big data is built up from small, everyday transactional data – such as bills of materials, inventories, production durations – and companies tend to not pay as much attention to its quality as they should. If data accuracy is poor, or even average, systems don’t yet have the capability to cleanse the data to an acceptable accuracy. If the data is then used to provide information that ultimately influences decision-making, and its accuracy is only 5 to 15%, the effects are felt throughout the organisation.
What are the current trends within manufacturing when it comes to data analytics?
Predictive maintenance is one area where IoT, big data and analytics are making a significant impact. Although it originated in the 1990s, the advent of advanced technology has meant that the capabilities of predictive maintenance have recently been ‘supercharged’, particularly in the manufacturing sector with smart factories becoming a reality. Unplanned downtime and poor maintenance can cost companies millions, but IoT-enabled sensors can detect when machinery needs a check-up, preventing the development of a more serious fault which would cause costly disruption. Not only does predictive maintenance identify errors missed by the human eye, but it also makes solely data-driven decisions to improve the lifespan of machinery, lower service costs and increase operational efficiency for healthier profits.
What is the best strategy for driving the best business value from data analytics?
A surprisingly large number of companies have the budget to buy data analytics technology but lack the plan to implement it effectively in their business. This requires consideration of strategy, processes, and vitally, people and their capabilities and behaviours. Pivotal to the translation of data into valuable information is having the right people analysing and interpreting the data – you need a good data analyst. These are highly talented individuals with a very particular skill set; they take aggregated data and analyse it to reveal insights regarding not only how organisations operate, but how customers shop. A good data analyst will help organisations create an accurate picture of changing demand, based on the current realities of consumer behaviour, and understand what is driving purchasing.
Looking to the future how would you like to see this technology developed within the industry?
Despite Industry 4.0, IoT and AI offering so many benefits, most businesses – even the ones who have invested in the technology – are currently failing to extract the value from the data they’re collecting. A recent study cited that although 54% of companies in Europe are using Industry 4.0, most of them have barely scratched the surface to tap into its true potential. Reasons for this include inadequate data, lack of organisational maturity, a shortage of the correct skillset or investing in the wrong systems. Organisations need to develop a greater understanding of what they need to do to successfully integrate data analytics into their business plan; dedicating time beforehand to establishing what information they want, what purpose it’s going to serve and how they’re going to manage it, in order to reap the benefits that digital technologies can offer.
Could you tell me a little bit about your company?
Oliver Wight EAME are global business transformation specialists with over 50 years of experience helping some of the world's best-known organisations reach and sustain excellent business performance. As pioneers of Sales and Operations Planning and originators of the fundamentals behind supply chain planning, Oliver Wight professionals are the acknowledged industry thought leaders for Integrated Business Planning.
How is your company using data and data analytics within your company?
For any organisation using, or considering, advanced technology systems to help them analyse their data, this needs to be fully integrated with their overall business plan and strategy in order to achieve the best results. This is where our work comes in. We work with senior management to implement Integrated Business Planning (IBP), a process that aligns company plans, people, processes and tools to effectively deploy the strategy. As part of this, our partners assess where clients are in terms of maturity and determine their capability for accelerating improvement and driving the right decisions on technology and tool integration. Maturity level identified; our clients can subsequently make decisions as to when and what technological tools they can introduce to align not only with their current capability, but also help to realise their strategic goals.