Analytics: Predictable way to stay competitive
Organizations are collecting more data than ever from their own operations, supply chains, production processes, employees and customer interactions
We are in the middle of a data explosion, brought about by rapid technological advancements that have considerably aided the process of data capture and storage. In an increasingly connected world, data is pouring in from all directions—posts to social media sites, purchase transaction records, information recorded on smart meters, to name a few. Organizations are collecting more data than ever from their own operations, supply chains, production processes, employees and customer interactions. But extracting meaningful insights is the single biggest challenge that this massive data surge poses and hence, the strong emphasis on analytics.
Enterprises are looking to make analytics all-pervasive by implementing them for all of their key growth drivers, including operational efficiency, customer service, customer experience, human capital, product development and pricing strategy. Rather than being confined to a select few functions, analytics is now being embraced by almost all business functions for improved decision-making and business outcomes. The fueler has been the global economic environment that is literally altering the way enterprises think and conduct business.
Today, organizations operate in an environment characterized by increasing expenditure, cut-throat competition, shorter time-to-market, stringent regulatory compliances and changing customer behaviour. Given these factors, enterprises need to be lean, innovative and pre-emptive while making real-time decisions. Analytics has thus emerged as the key competitive differentiator, driving actionable insights to help organizations make conscious strategic decisions.
The predictive and prescriptive nature of analytics has meant that enterprises are increasingly posing the right questions. They find themselves in a position to predict the direct consequences of a certain action and identify how the outcome will change if that action is not effected.
For example, airlines and telecom companies are leveraging analytics to accurately identify potential churn and prevent it by designing incentive and marketing programmes for specific customers. Retailers are making their marketing efforts targeted and shopping experience more personalized by tailoring their offers to the individual buying patterns and frequencies of customers. Enterprises are improving their internal practices by making their processes such as human resources and procurement more strategic to the business.
The ability of analytics to combine data from disparate sources and analyse to a granular level has made it significantly easier for pharmaceutical companies to aggregate data from distinct sources, including clinical trials and insurance claims, and accurately predict drug pricing and effectiveness. Similarly, enterprises across industries are better evaluating the efficacy of their human capital by combining personal performance data with business data. Thus, it is hardly a surprise that traditional data warehousing projects are rapidly giving way to advanced analytics that has the propensity to analyse unstructured data and unearth hidden patterns cost-effectively.
The global analytics market that has averaged a growth of 30% year-on-year has been further boosted by the availability of analytics solutions over the cloud, which has reduced entry barrier levels for organizations. Enterprises that were hesitant initially are now leveraging analytics due to the reduction in costs. The analytics outsourcing market has also grown at the rate of more than 35% CAGR (compound annual growth rate) and is expected to scale $6 billion by 2016.
The successful implementation of analytics is as much about having the right tools as it is about having the right people working on them. Extracting insights from data is hardly trivial and the success of any analytics programme will depend on the ability of the professionals to accurately derive working models from the data to drive penetrating outcomes. Experts predict there will be an acute dearth of mathematicians and statisticians in the foreseeable future, impacting solution buyers and service providers alike.
Considering the growing relevance of data scientists, the need of the hour is specialized courses in analytics to effectively address the skill gap, helping the BPM (business process management) industry move up the analytical maturity curve.
To conclude, analytics has turned out to be the clear game changer by broadening the business horizons. Decisions that were earlier driven by gut instincts are now being driven by hard-hitting insights. There is a clear shift in strategy brought about by sharp visibility into business operations. But as more companies gear up to implement analytics, they should first address the critical issues of organizational readiness, operational and cost constraints, risk and compliance, technology convergence, and the availability/unavailability of specialized talent.
The author is group CEO of IT services company WNS Global Services Ltd and chairman of BPM Council of software lobby Nasscom.
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