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Having sat through numerous presentations and demonstrations and listened to marketing directors arguments, I am convinced more than ever of the value that big data analytics can bring to the top line. Evidence abounds with ROIs and financial case studies that Big Data analytics helps make targeted and personalised offerings to customers, predict future trends, reduce revenue leakage, gain market share and more.
Much has been written about the benefits of market facing big data analytics. However, little has been mentioned about how big data analytics benefits enterprises internal operations.
Here are some thoughts and insights on that.
| A recent survey on 'Rethinking HR for a Changing World', conducted by KPMG with the Economist Intelligence Unit indicated that 57% of HR Executives rated workforce data analytics for business intelligence as a focus area. Josh Bersin an HR analyst, opined in a Forbes article that HR functions have been collecting myriads of data for the last several decades, including demographics, educational history, job location and many other factors about employees but not using it scientifically to make people decisions.
Big data analytics can support your talent acquisition strategy and help make HR more efficient. For e.g. by providing a clear understanding of your present skill-base and requirements for future skills, the recruitment strategy can be customized to be more effective. It gives the talent acquisition processes, access to information outside the resume that can be verified easily there reducing overheads in the recruitment process. Analysis of unstructured data, particularly from professional social media portals like LinkedIn and Glassdoor will give organisations a bigger resource pool to cast their net in. It could help the human resource teams understand reasons of attrition and benchmark competitor compensation. Intranet discussions can be analysed to get to the bottom of the employee dissatisfaction quickly and keep employee productivity high.
Operations within an organisation can be streamlined and managed effectively with big data. The International Society of Automation (ISA) which has, since its inception in 1945, worked with over 30,000 members to help solve technical problems through automation. It notes several benefits of big data analytics in operations management. Modern manufacturing shop floors are highly automated with large volumes of data collected from digital equipment, production lines, sensors, time log machines and suppliers, yielding information such as human cycle time and system throughput time, raw material arrival time etc. But the diversity of data formats in the data collected from various automation systems presents a challenge for analysis. According to the ISA, while manufacturing operations generate massive amounts of this big data, much of it is unused or discarded. But in recent times, manufacturers are beginning to report substantial cost savings or new revenues resulting from big data insights.
Big data can be thought of as a mash-up from all these systems which can answer specific questions, e.g., what was happening in the various automation systems, when a certain manufacturing defect occurred and can occur in the future; or tracing all the parts made by a machine that was out of tolerance, or how an out-of-tolerance condition in a particular manufacturing cell would affect customer orders.
Big data analytics will enable smoother operations management by anticipating chinks in the process chain, machine down time and enable proactive measures to oil the machine. Supply networks can be worked more effectively by understanding their behaviour patterns and the factors constraining them. The list is endless.
The finance function has grown beyond merely supporting the business to being the gatekeeper of business critical information. Analysing financial information and communicating it to operational decision makers is of paramount importance and this can be done easily and more effectively with big data analytics. According to a global trend study conducted by Tata Consultancy Services on big data initiatives, a little more than half of the respondents said they had undertaken Big Data initiatives in 2012. When asked whether big data initiatives had improved decision-making, an overwhelming majority (81%) said they had. According to the study, finance and accounting managers see the most value in Big Data for the two activities: measuring risk and improving budgeting and forecasting. Analysis can reveal bad credit clusters, help identify areas of internal and external theft and assist in determining appropriate financing amount for customers. With capital required to run the business and operational risk having a tight correlation, using big data analytics will provide the predictability to manage fluctuations in capital needs easily.
I hope I have given you some sense of how big data analytics initiatives are amongst the few that offer the most gains to stakeholders whether looking outward to the market and customers or looking inward to operations and finance.
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