Business Analytics is the practice of using data to drive business strategy and performance. It is undergoing massive, disruptive changes that will radically transform the way the industry and customers think about analytics. The exponential growth in data is a key driver of this change. In one of its research IDC predicts that by 2020, the amount of high-value data worth analysing will double and 60 percent of information delivered to decision makers will be actionable. Adding up to the massive increase in disposable data, the mainstream adoption of cloud computing across the enterprise continues to put pressure on the capabilities of businesses to incorporate all relevant data from multiple data sources to enable users to make more timely, comprehensive, insightful business decisions. All this adds up to Business Analytics demand by companies for new tools and techniques to quickly and easily collect all types of data, and to store, manage,integrate, manipulate, aggregate, analyse all that data into useful information that positively impact their businesses.
Following are some of the key future trends that may shape the practice and application of Business Analytics globally across industries:
1. Cognitive technologies & Computing gathered more than $1 billion in venture capital funding in 2014 and 2015. The overall market revenue for cognitive solutions is expected to exceed $60 billion by 2025. A recent IDC research shows that cognitive systems will be a major disruption and will significantly impact businesses, healthcare, work, society and economies. Further, the report predicts that by 2020, 50 percent of all business analytics software will incorporate prescriptive analytics built on cognitive computing technology. In a nutshell Computing involves analysis of images apart from text using a natural language interface and make the machine to learn very close to the way humans learn. A classic example is the driverless car talked about. One cannot learn driving by simply reading books. By analysing the images the way human driver drives and takes decisions in various circumstances we can make the machine learn. The advanced and predictive analytics software market is projected to grow to $3.4B in 2018, attaining a 9.9 percent compound annual growth rate from 2013. IDC notes that simplified tools provide more intuitive graphical user interfaces and easier-to-use features are fueling business analysts adoption.
2. The amount of data in our world has been exploding, and analysing large data sets – so-called big data – will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus, according to research by MGI and McKinsey’s Business Technology Office. Leaders in every sector will have to grapple with the implications of big data, not just a few data-oriented managers. The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data for the foreseeable future. However, several issues will have to be addressed to capture the full potential of big data. Policies related to privacy, security, intellectual property, and even liability will need to be addressed in a big data world.
3. A report released last spring by the McKinsey Global Institute predicts that by 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.
4. The Internet of Things (IoT) is no more limited to just the gadgets; it is rather integrating to a wide range of things, including humans to form new business models — think Uber — and influence it on had peoples behaviors. International Data Corporation (IDC) estimates that the worldwide IoT market will grow from $655.8 billion in 2014 to $1.7 trillion in 2020. Devices, connectivity, and IT services will likely make up two-thirds of the IoT market in 2020, with devices (modules/sensors) alone representing more than 30 percent of the total.
While it is evident that application of business analytics will continue to impact the business and future industry trends, it is worthwhile to note that there is an acute shortage of skilled manpower in this area.
Despite the surge in data science related programmes, universities and colleges are not able to produce effective and efficient data scientists fast enough to meet the business demands. More importantly, they certainly cannot produce experienced data analysts or scientists from their one or two year programmes; leave aside the shorter duration ones. To complicate matters, there is no clear set of capabilities that define a ‘business analyst because different problems require different skill sets. To combat this, some organisations are taking a multipronged approach by supplementing campus recruiting with alternatives – from turning to managed analytics to cultivating in-house talent.
IFIM B-School launched the executive PGDM programme in September 2014. The programme has garnered significant attention from corporate world as well as practitioners. Professionals from various companies such as IBM, Genpact, TCS, Herman Miller, Schneider Electric, Fujitsu, United Healthcare, Mindtree etc., having different career aspirations, have enrolled for the programme. So far the programme has helped more than 100 business professionals to change or accelerate their respective career paths. The success story of the programme has recently been featured on IBMs website. Based on the success of the programme on all relevant aspects, IFIM Business School has been recognised by IBM for building capabilities for management students and Working Professionals on Big Data & Analytics using IBM software.
The programme duration is 15 months, is AICTE approved and is uniquely designed for a hybrid model of delivery. The architecture of the course clearly depicts that emphasis has been laid on training and making an individual gain expertise in all the important pillars of Business Analytics, i.e., Business Acumen, Domain Knowledge, Tools and techniques, and problem solving capabilities. The programme also contains a real life project that provides an opportunity to individuals to apply their conceptual and technical understanding of solving a business problem in hand. The course curriculum was designed to offer poise between key business concepts with skills in analytical, statistical modeling and data management.
The programme has been taught by highly experienced in house faculty as well as experienced faculty both within and outside the country.
A Center of Excellence in Business Analytics is also established at IFIM to strengthen the academic/industry interface in Analytics.
The author is Dr Chandrasekhar Subramanyam – senior professor and director of the Business Analytics Centre in IFIM, Bangalore.
