That analytics is a much-heard industry buzzword now is not without reason. Most experts believe that the use of analytics can help IT decision makers to make better and faster decisions and automate processes. It enables them to build a solid foundation of strategic analytics products and services to take advantage of all of the data sources, including structured and unstructured data.

 

Factors Driving Analytics

Business Analytics (BA) has been a hot topic of discussion amongst industry experts  since almost two years now.  Research groups have estimated that the analytics market stands at $17 billion worldwide. Most industry verticals including the government, BFSI, IT and manufacturing sectors started depending on analytics in a big way owing to the development and support, and for localisation needs. A large fraction of the banking segment depends upon BA for diverse needs, achieves better outcomes, and derives better customer satisfaction.

For instance, SBI is the largest user of analytics. Some of the functions that the bank is keen on using analytics for are executive reporting systems, new recruitment process, judging the propensity of employees, getting monthly sales updates and sales forecasting, etc.  One customer, Asian Paints, uses analytics for sales forecast and operational maintenance, as an extension to Business Intelligence.

Leading companies across various industries are using the insights they glean from analytics to achieve significant outcomes in areas such as customer satisfaction and retention, operational efficiency, financial processes, and risk, fraud and compliance management. Under analytics, about 300 customers are using predictive analytics tools for varied functions. In the case of analytics, investments are measured based on the sales performance after using the tools. About 20 to 30 banks monitor sales performance with analytics. Another example is that of the insurance sector which uses analytics for creating product differentiation in the market place. Indeed, analytics has been the game-changer for many enterprises.

 

When and Where to Use Analytics

There is not an iota of doubt that analytics will turn insights into outcomes which is why most customers are fascinated by the technology. The challenges have been many for IT heads who struggle to feed the line of business with accurate figures and factors and the market pulse. Unlike other technologies, analytics is driven by finance, HR, marketing and other business groups and not so much by IT. The new trend is that the discussions and negotiations are carried out in the line of business.

 

Implementation Steps

There are a few tasks that IT managers need to remember before jumping into full-fledged deployment. It is critical to carry out a pilot implementation project on analytics. It is important to test the waters and understand the impact it makes on the business.

IT teams need to attend informal workshops and have some initial discussions with the business to understand how it should be taken forward, in a way through which it can co-exist with the other tools.

Another vital aspect is having a right choice of partner or partners, gaining insights into the problems and the integration process. After a thorough analysis, a value statement needs to be created on what can be construed as success and which can be measured.

IT heads can use a specific type of dashboard, and deploy predictive analytic tools to measure the outcome. Most often, the scale of implementation matters; this determines the RoI.

Take stock of unstructured and structured data using BI tools. Use data mining tools to map the data and transcript the same.  Have security agencies deploy resources to form policies and analyse data to assess  potential threats. The data should be analysed in real time.

Technically speaking, the use of BA does not need a BI or data analytics. A well defined pilot project can be implemented in three months. IT, along with business and finance departments, plays a big role in zeroing in on analytics.

 

Pay Backs

It would not be an exaggeration to say that analytics would definitely help CIOs when they are unable to plan a budget or handle a complex situation. It will help in having set up a tool to understand KPIs of the company. By embedding insights into actions across the organisation, one can gain clear insights into all areas of business—customers, competition, and the market, giving the business the ability to predict trends before they happen. To state an example, HMEL, a joint venture between Hindustan Petroleum Corporation Limited (HPCL) and Mittal Energy Investment Pte Ltd, Singapore, has adopted a new IBM analytics-based solution to transform how the company manages its financial and operations data to boost business performance.

HMEL has built the 9 MMTPA (million metric tonne per annum) Guru Gobind Singh Refinery in Bathinda, Punjab. The first oil and gas project to be set up in Punjab, the refinery produces petroleum products complying with Euro IV emission norms, with a capability of processing 180,000 barrels of crude oil per day.

The analytical solution integrates information from the various components of the MES, enterprise resource planning (ERP), and control systems within the refinery and delivers a consolidated, single view of the data. The technology enables HMEL to analyse key corporate business processes including planned versus actual investments, production, key performance indicators, among others. The system generated near real-time information for HMEL business executives to use to make more intelligent decisions regarding optimising productivity and margins.

The IBM analytics solution not only delivered the ability to access data consistently, but also equipped the organisation with the power to interpret, transform and derive process operation actions from the information. The industry standards based information model and associated integration techniques enabled HMEL to turn data into information that could be accessed and delivered through Web services.

 

Analyse to the best

• Best practice is to have a clearly drafted problem statement or statement of purpose for analytics
• Have quality and adequate data on hand before implementing BA
• Stakeholder's expectations need to be clearly articulated
• Do not make a big bang approach to deploy analytics for all functionalities
• Use the existing data as a trial
• Try out a cloud model for trying out analytic tools or licenses
• Work on an on-premise solution with a client to bring out the first report

“Most industry verticals including the government, BFSI, IT and manufacturing sectors started depending on analytics in a big way owing to the development and support, and for localisation needs”