BUSINESS INTELLIGENCE AND ANALYTICS TRENDS FOR TODAY'S BUSINESS

Knowledge is Power. This statement holds true now, more than ever, thanks to the wealth of data that is generated on a daily basis. An IBM Report titled ‘10 Key Marketing Trends for 2017’ states that 2.5 quintillion bytes of data is generated every day, 90% of which was created in the past 2 years alone. And it’s data that businesses are constantly trying to tap into, in order to understand their users better and drive revenue growth. Hence, the rush to invest in data and data analytics in recent times. IDC’s (International Data Corporation) ‘Worldwide Semiannual Big Data and Analytics Spending Guide’ reports that worldwide revenues for big data and business analytics is estimated to grow from $130.1 billion in 2016 to more than $203 billion in 2020.

But, what good is data, if you can’t make sense of it. Only 1% of data is actually analyzed. That means insights are drawn from only 1% of data, business decisions are taken based on only 1% of data. Additionally, poor or bad quality data can cost a company 20-35% of their operating revenue.

This is where Business Intelligence (BI) and Business Analytics (BA) come to the rescue. Effectively implemented, they can radically boost a company’s sales, by ensuring that relevant actionable insights are drawn through proper analysis of the data collected. Gartner defines Business Intelligence as ‘An umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance.’ And it defines Business Analytics as follows, ‘Business analytics is comprised of solutions used to build analysis models and simulations to create scenarios, understand realities and predict future states.’

While, often used interchangeably, BI and BA have certain important differences. BI looks at the past and present data, to tell you what happened and is currently happening. By analyzing the past, and showing you the present in detail, it helps you create a model for reactive response. It aids you in deciding what works and what doesn’t, so that, going forward you can incorporate the processes that work, while eliminating those that don’t. BA, on the other hand forecasts future outcomes, using sophisticated statistical analysis, data mining, and predictive modeling. With BA, you can anticipate the future and prepare for it, by developing a model for proactive and preemptive response. Both aspects are necessary for a business to function successfully, as real-time data allows you to respond to ongoing problems in the best possible manner, while foreseeing the future allows you to prevent issues before they arise.

BI and BA successful use case

Companies the world over are successfully using BI and BA to not just make themselves more efficient, responsive, and proactive, but also to improve customer experience, which should be the ultimate goal of any company that wants to thrive in the current customer-centric era.

Macy’s – Using analytics software installed into the company’s database, the offline and online platforms of this international department store can analyze gigantic amounts of data on a daily basis. And the data analyzed includes social media platforms, particularly twitter, apart from regular store transactions. This has helped the retailer understand customers’ buying behavior, such that it can tailor promotions and products to better cater to their needs. The result: improved margins, increase in store sales by 10%, and simplification of operations across departments. The beauty of BI and BA is that they allow you to apply data in unique ways. For instance, Macy’s is able to forecast in-store sales based on specific weather patterns, while also altering the prices of products based on if they are deemed ‘’hot or not”.

5 Key Trends driving BI and BA

BI and BA are propelled by a host of technologies. Some of the main tech trends supporting the rapid rise of BI and BA are as follows:

1. Self-service BI :
Self-service BI characterized by self-service machine data analytics, self-service data discovery and explorations, and analytics on the cloud is a result of business units driving IT requirements, and BI systems and BA tools being used by business units without the interference of the IT department. Self-service BI being more interactive and user-friendly can be easily used by the non-tech business users to make relevant, actionable, and timely decisions. Additionally, the opening up of BI beyond the IT department, makes the business more agile. Self-service BI being on the rise, more companies are investing in BI systems that can be housed on the cloud and are capable of multiple functions like storage, integration, analysis, and visual representation of data, as opposed to multiple different tools.

2. Analytics :
Analytics is at the core of BI and BA. Predictive and Prescriptive Analytics are the two major categories that dominate the BI field. Predictive Analytics, as the name suggests, looks to forecast the future, by extracting and analyzing information from the past and present. Spotting trends, opportunities, and potential problems is the chief aim of predictive analytics. Two methods of Predictive Analytics currently popular are Artificial Neural Networks (ANN) and Autoregressive Integrated Moving Average (ARIMA). Prescriptive Analytics is concerned with analyzing data to determining the right steps that should be taken to achieve a particular goal. It tries to comprehend the effect of future decisions, so that any precarious moves can be adjusted even before they are made. Machine learning, graph analysis, simulation, heuristics, complex event processing are some of the techniques that form Prescriptive Analysis.

3. Artificial Intelligence (AI), Machine Learning (ML) and Cognitive Computing :
AI has been ranked No. 1 in Gartner’s 2017 Strategic Technology Trends report.AI, ML, and Cognitive Computing are fast becoming main-stream. Companies are embracing text analytics, language processing, speech recognition, virtual agents, automation, machine language and deep learning platforms in a bid to collect, store, integrate, analyze, and respond to data faster. As data volumes and complexity increases, algorithms created to process them get smarter along the way, through their self-learning capabilities. Billions of rows of data can be processed in seconds. This means real-time relevant data is available to companies, giving them insightful information right when they need it.

4. Cloud :
The benefits that the Cloud offers continue to enhance its role in modern day business. As a number of cloud based services for data management, processing, computing, and analytics are being churned out, the reliance on in-house systems is decreasing. Cloud provides the kind of affordable accessibility that makes it attractive to small and medium businesses as well, thereby increasing the reach of BI and BA. Additionally, in this era of mobility and IoT, Cloud allows for anytime/anywhere flexible access to data, which is no longer a luxury, but a necessity, if a business wishes to serve its clients satisfactorily.

5. Data Governance and Security :
Gartner analyst Merv Adrian advises, “Well-managed data is mandatory before you move to advanced analytics. Build controls for your Big Data & Advanced Analytics Pipeline (BAAP).” As self-service BI is on the rise, there is a stronger need for governance and security measures. A mechanism has to be put in place that permits the freedom to explore and interpret data, at the same time ensuring data is not misused, and there are no breaches. Bimodal IT offers solutions that set standards for how data should be used, and provides controls to keep data access in check, thus, enabling governance and ensuring security. That being said, data governance measures shouldn’t restrict a business’s ability to be agile. The right balance between governance and agility should be struck.

Looking Ahead
BI and BA are slated to become mainstream aspects of any and every business that wants to stay competitive. Irrespective of the scale of implementation in a business, they have established themselves as vital tools for sustainable business growth.