Leaders at Wipro Technologies give insight into the relevance of big data technology trends to manufacturing companies.
Over the last year, the technology media has been dominated by headlines about the challenges posed to businesses, in managing ‘big data’ and the ‘data deluge’.
Organisations are being forced to re-assess the ways in which they store, manage and analyse their data across sectors, ranging from healthcare to retail, financial services to utilities; and the manufacturing industry is no exception.
Given the numerous stages involved in manufacturing processes across operations, production and the supply chain, the quantity and type of data generated from multiple and disparate sources is huge.
Identifying big data in manufacturing
In simplistic terms, big data for manufacturing can be the data generated from machines, devices, telematics, social sources and more.
Harnessed in the right way, this plethora of information has the potential to transform the way a business operates – lowering manufacturing cost, reducing warranty costs, introducing new products and services, rationalisation of supply chain and inventory, to name a few.
Making big data useful in manufacturing
However, finding the right business case to make sense of such a wealth and variety of data is important. Some of the key use cases for leveraging new age data are improved customer service and effective warranty management by leveraging device data analytics, better inventory management using telematics data, reduced equipment downtime by means of machine data analytics (data generated from the machines used for manufacturing products).
Trying to analyse big data to generate an integrated and complete image of one’s business can seem daunting. According to a recent survey commissioned by Wipro and conducted by the Economist Intelligence Unit, of over 300 businesses, only one out of six manufacturers have data management strategies in place to collate large volumes of data. The task of integrating big data into traditional IT infrastructure requires a right mix of processes, technologies and talent.
Crafting a big data strategy
Firstly, consider the business case for data analysis. Although it is important to source as much information as possible from all parts of an organisation, not all of this data is likely to give relevant business insights. Organisations must identify which business processes are likely to benefit from data analysis, and go from there, rather than taking a broad brush approach.
Secondly, in order to build a strong foundation, one must base-line the data processes and identify data sources, before undertaking the data journey. One needs to identify data which is relevant to one’s business, from the overall data universe. And identify external and new age data sources to plug gaps to implement a robust system for data governance.
Thirdly, it is important to identify gaps in one’s current technology landscape and select best of breed technologies, to complement the existing IT infrastructure to handle external and new age data. Also, it is important that appropriate technologies are leveraged for data dissemination, visualization and predictive analytics.
Data is becoming more complex and disparate than ever before and it is not something that organisations – particularly those in the manufacturing industry – can ignore. Integrating data from multiple channels and sources can pose a challenge, but with the right approach the results can be overwhelming: improved business operations, streamlined process and, most importantly, increased visibility across the organisation.