Sarah Walker explores how making the most of big data can help manufacturers steal a march on the competition.
Without a doubt, initiatives such as lean manufacturing and six sigma have enabled manufacturers of all different sizes the world over to realise significant efficiency savings - reducing waste, eliminating bottlenecks and ultimately saving businesses money. But the complex nature of many manufacturing operations means even with seemingly efficient processes in place, there are still major savings to be made by taking a more granular, in-depth approach to optimising operations. The key to achieving this elusive competitive edge is data.
As we know, the increase in technology across all areas of manufacturing has led to a huge rise in the actual volumes of data generated. The real challenge is how to make the most of this ‘Big Data’. Many businesses are very good at collecting and storing vast swathes of data, which they then duly use for tracking and monitoring, but it’s those businesses who go on to further analyse this data that have started to derive real value from the information. It’s only with this deeper analysis that manufacturers can draw actionable insights, identifying additional opportunities and using them as a basis from which to optimise business processes.
This isn’t something just for larger organisations either. The main barriers to big data analytics in the past were the fact that the data was often held in department-specific systems or spreadsheets, which would not only be time consuming to amalgamate but with the added risk of the inevitable errors that the rekeying of data brings. Once unaffordable tools such as CRM, ERP, SCM and BI, to name but four, are now at a much more manageable price-point for SMEs, helping manufacturers of all sizes to identify once hidden information at the click of a mouse. This is further helped by the wide availability of big data analytics via the cloud, solutions which help to clean data and identify any errors, as well as pinpointing the areas for improvement and the all-important actionable insights which are the springboard to timely, informed and robust decision-making.
By aggregating data from multiple disparate sources and then using analytical tools to determine interdependencies, patterns and relationships between different processes, big data analytics can have a tremendously positive impact on many areas of the business. For example, the ability to precisely locate the root causes of problems improves quality across the board, and the big data tools which can capture and analyse when and how often a product is produced, scrutinising time and cost efficiencies, can help to improve yield. When it comes to customer service too, the context that big data analytics tools provide to field product performance or service, in combination with customer data, provides the means to better understand, manage and control the customer experience.
Although still in its relative infancy, big data isn’t a new concept for manufacturers, but for many, making the most of this data might still seem a step too far. It’s only with the right analytical tools in place that manufacturers can make sense of the ever-increasing amounts of data that they’re faced with every day. The predictive insight that results from advanced analytics underpins smarter, faster decisions, increasing business agility, efficiency and productivity, positioning manufacturers apart from their competitors and setting them on a course for success.
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