Business intelligence: CIOs’ top priority

by Darinia Khongwir    Feb 25, 2013

Business Analytics
The worldwide Business Intelligence (BI) software revenue will reach $13.8 billion in 2013, a 7 per cent increase from 2012, according to Gartner, Inc. The market is forecast to reach $17.1 billion by 2016. A CIOs’ appetite for BI is complemented by more-tactical buying in business units for departmental and workgroup analysis, as well as for personal BI, enabled cloud, mobile, social and information that are the fundamental drivers.

“BI and analytics have grown to become the fourth-largest application software segment as end users continue to prioritize BI and information-centric projects and spending to improve decision making and analysis,” said Dan Sommer, principal research analyst, Gartner. “As more and more information is generated, business models need reinvention, and it’s increasingly clear that mastering analytics on big data will be a key driver for the next economic cycle.”

In large corporations the growth drivers for BI are varied and manifold. BI and analytics are increasingly becoming a top investment priority for CIOs across the globe and more Indian organisations are in the process of adopting BI. One of the reasons for making this a top priority for CIOs and CXOs is because they see this as the next competitive advantage.

“As far as processes are concerned, the adoption of Enterprise Resource Planning (ERP), Human Capital Management (HCM) and Customer Relationship Management (CRM) solutions, have not shown that much advantage through process expediency. So the next wave of competitive advantage is understanding information, analysing the information and arriving at a better decision-making stage – whether the decision-making is at the board-level or the field person(s),” said Vikash Mehrotra, Director, EPM/BI, Oracle India.

Self Service BI
According to Peter Wren-Hilton, CEO, Pingar, BI can be used to represent what is considered a stack. The stack consists of data visualization, self-service BI, and data mining. “Data visualization is what most organizations are thinking about when they use the term BI. Taking information and representing it in a graphical way that aids decision making. This use dominates the solutions available, and it’s implementation fairly intuitive. In the last 10 years self-service BI has become popular—the ability for individual users to manipulate cubes of data for better insights,” he said.

Data mining is a much broader category that includes all the advanced and automated algorithms for interpreting data. Most organizations have the wherewithal to embrace data visualization and self-service BI. But data visualization is still the most common. Few organizations are yet ready for the broader data-mining category. Perhaps they are technically equipped, but fall short because their storage and information architecture of data is very poor. “Perhaps they don’t even know where the data is, but they know they have it. Or perhaps the relationships between one data source and another have never been established. So even with the right tools they are unable to start. For these organizations the focus has to be put on better quality of information. And answer questions such as “where does unstructured content fit in our big data paradigm?”. We think the adoption of more and more NoSQL platforms will aid in getting more organizations to the data mining stages,” said Wren-Hilton.

Uptake of BI in SMBs
It is not just large corporations who are bothered about BI and analytics tools. Both are seeing a huge uptake in small and medium businesses as well. Indian SMBs are increasingly realizing the need to take faster decisions based on real-time analysis from large volumes of data. As a result, they are turning to BI solutions for greater efficiency.

Indian SMBs as well as larger organisations such as Wipro, Cognizant, Infosys, TCS are clearly looking at the value-added services that Business intelligence tools bring in to the Enterprise Content Management (ECM), Customer Experience Management (CEM) and HCM practices and will soon see such focused efforts paying rich dividends in the retail sector, insurance and healthcare, to name a few.

“What we have seen is an increased awareness about what it takes to bring content into BI systems to get the best results and presently CIOs in large enterprise segment including financial services, insurance and manufacturing have shown maximum adoption. With the emergence of business analytics and intelligence solutions, we are expecting that the usage of BI will soon expand beyond these verticals, showing greater adoption in the SMB segment,” said Wren-Hilton.

BI for government agencies
Traditionally speaking, a decade ago, an organisation having ERP/HCM/ CRM systems in place would probably take up a BI project as an MIS project. These are typically small to mid-sized projects affecting 50-100 people in a large-sized organisation. Today, organisations that started with an MIS requirement have moved to BI across all verticals. And this trend is not limited to one or two organisations. It is evident in large B2C organisations including insurance, banking, telecom and even the government-run institutions have seen a large uptake in the adoption of the technology.

“For example, tax authorities in India would want to know what are the kind of tax collections and the segments they are collecting the most taxes from; what are the segments where the taxation leakages are more prominent – in terms of liability of collections; how the time period can be reduced so that the money can be in the government coffers as soon as possible. These kinds of analytics were made available to the tax agency to help them better their tax collection; reduce the cost of tax collection and give them insights in to what segments to look at in terms of leakages. Similarly, a city council would get insights into how it is performing–if they have been able to deliver everything it had promised to the people. Government treasuries are also using BI solutions to better its budgeting and planning mechanism. Hence, the bureaucratic and political class are adopting technologies to spike up their efficiency,” said Mehrotra.

Issues surrounding quality of data
But at the same time quality of data is a major issue with many organisations as they can’t make sense of the data to gain any actionable insights. “Issues with quality of data can be isolated to a bad data source or sources. That is usually the result of a bad method of capturing information. For example survey forms that have poor content validation before submission. If at all possible organizations should find a way to disallow the poor quality data. “Garbage in garbage out”, it may not be worth organizations’ time to try to improve bad data sources so elimination, although a harder answer is the better one. For now. We see that organizations are enjoying the approach of taking baby steps and being successful with one data source before they tackle new ones. This maximizes their time, and allows them to focus on what they know they can control and succeed at,” said Wren-Hilton.

“It is a continuous process. With the business complexity increasing, the more you will find data being processed. Ten years ago, an organisation will probably have analytics set up. The quality of the finance data would have been fairly consistent, but if you look at the HR data or customer data, that might not be available in detail and the quality of that data would have been suspect. But as organisations adopted CRM systems and HRM systems the data would get better. So, I would not call it a challenge, but new opportunities,” said Mehrotra.

Mobile BI
With mobility fast gaining ground, BI is no longer restricted to the distribution of business data over standalone devices. Finding actionable insights on the go for users who employ Bring Your Own Device strategy has to be accounted for. In today’s world, mobile business intelligence is seen as the next big thing in the industry.

“BI on mobile data is going to be huge. Not only big data analysis on the usage of devices, where they are used, what types of apps used in what types of markets. But also things like measuring the quality of a live concert, given the mobile activity on social feeds from that concert. Mobile devices are simply a form of capture except there are many more of them than traditional capture, and they are much more mainstream. A lot of the analysis that we want to do from PC created data will move to mobile,” said Wren-Hilton.

Open Source BI
On the merits of open source BI as opposed to proprietary software, Wren-Hilton said that most open source platforms are paid services in the form of consulting, support and so on. As a result there is no comparison on the quality of open source with that of commercial software licenses, or even SaaS. “They can all be compared equally. There are some open source BI platforms that are pushing the envelope, and others that are barely keeping up. Ultimately organizations have to consider the total cost of ownership of working with these platforms. Additional considerations for an open source system are: Will the platform be around? Will it continually be updated?” he asked.