When Analytics Is the Answer Are You Asking the Right Questions?

When Analytics Is the Answer Are You Asking the Right Questions?

Depending upon what you read, who you follow, the Business Intelligence and Analytics (BI&A) market is valued anywhere from $16.9 billion in 2016, to $41.5 billion through 2018, and expected to exceed $60 billion by 2025. It’s a huge, growing, global market fueled by ongoing innovation and seemingly endless opportunity. But why now? Why is the market potential so huge? What is making analytics the new in-crowd?

Analytics as defined by Deloitte Analytics in their report titled The Analytics Advantage: We’re Just Getting Started, is the practice of using data to manage information and performance, and has been around for at least 30 years, guiding cause and effect scenarios in almost every industry, any size business.

Until recently, analytics in business communications has been known as reporting. It has been buried in individual communications applications throughout the enterprise. To find out how successful an outbound dialing campaign was, run an outbound dialing report. To determine how many customers opt out of the IVR after 6 p.m. on a weekday, run an IVR report. To determine the quality of all the video conference calls employees hosted last month, run a video report. To determine any security issues in the network, run a report. All of these various reports are separate and typically require different skillsets to run them.

While these reports are full of all the intelligence ever needed about that one specific application, if you want a view of what happened across an entire omnichannel, multitouch journey (voice, self-service IVR, social, email, SMS, online, in-store) during a specific time period, someone will have to manually source, compile and sort all of that data for each separate touch point first. In other words, if you need the information on Tuesday, it will not be compiled, analyzed and put into a consumable format until Friday at best; most likely it will be Monday evening. And this is 2016.

As recently as last year, investing in the right analytics application finally became a priority for any size business, not a nice-to-have. In fact, Gartner reports that by 2018 more than half of large organizations globally will compete based on advanced analytics and proprietary algorithms. By 2020 predictive and prescriptive analytics will attract 40% of enterprises’ net new investments in business intelligence and analytics. Yet, only 50% of the chief analytics officers will have gotten it right.

Meaning, the rush to deploy analytics is overshadowing having a clear understanding of exactly what the business wants to accomplish with analytics. First understanding what the business is trying to accomplish determines which vendor and which analytics application are best needed to meet the objectives.

In my experience, most businesses that are making analytics an urgent investment are doing so because they want to be better positioned to (1) compete more successfully and (2) grow their business to increase revenue potential. In manufacturing for example, analytics becomes an urgent investment when companies need to analyze their processes and operations. Process data is not just for tracking purposes, it’s also for improving operations. When operations can be improved upon, business can improve.

In business communications, we look at two distinct groups: internal employees and external customers/partners. The first question analytics helps us address is: Are these groups getting what they want when they want it? The second question is if they are not getting what they want, when they want it, how can we fix it?

When they are getting what they want when they want it, then internally individual and team productivity should be up, processes and operations should be streaming along and efficient. Overall company performance should be at its peak. Externally, customers/partners should be happy and loyal. It’s about the experience—employee experience and customer/partner experience—people have when they interact with the company. It really is that simple. But getting there is not so simple, which is why analytics is needed.

Ironically the need for analytics is more visible in established companies. Companies that are established have typically passed the hurdles that most start-ups face: running out of funding, being squeezed out of the market by the competition, disappearing signs of growth, unable to pivot for survival in an unstable economy, etc. An established company can be a couple years new or 100 years old. Established companies typically have an enterprise infrastructure that has evolved over time into a complex system of un-integrated silos of solutions. Some of the solutions have been consistently upgraded while others have been barely maintained, yet others have been completely abandoned and need to have all the data migrated to somewhere accessible. Most established companies need to undergo a full transformation to be current and enable the company to utilize analytics effectively in order to compete.

Digitization of the Enterprise and Analytics

One of the most talked about transformations today, is digital transformation. With the digitization of the enterprise, the expectation and realization is that everything can be integrated and made to run faster and more efficiently. Once the enterprise is digitized, there is no longer a need to have separate reporting functions for each communication. Those reporting functions buried inside each application will be able to feed the right information and right events into the single, enterprise-wide analytics application. Aristotle said it best, “the whole is greater than the sum of its parts.” In our case, the holistic view is considerably more valuable than compiling a bunch of individual reports.

With a single analytics application it becomes much easier to have a single view into the entire journey—of customer data, partner data, employee data, process data, etc., no matter the channel(s), external or internal medium(s), system(s) or platform(s). Rather all data will feed into what’s called a data lake, which aggregates raw data in multiple formats. From the lake, the data then gets sourced into the four analytics buckets: descriptive, diagnostic, predictive and prescriptive insight.

  • Descriptive Analytics uses data aggregation and data mining to answer the question: ‘what has happened?’

  • Diagnostic Analytics is defined as a look at past performance to determine what happened and why. It answers the question: ‘why did it happen?’

  • Predictive Analytics is the ability to look at current trends within the business and project into the future what to expect based on those trends. Or, it can analyze data with a particular goal in mind and provide the probability of attaining that goal under current conditions. It answers the question: ‘what could happen?’

  • Prescriptive Analytics is defined as the ability to advise a variety of future actions and guide the user toward a solution. It answers the question: ‘what’s next and why?’

Each bucket of data can be further sourced to learn the journey and gain insight into how successful was the experience with the business during any event or action. Finally, a single view of everything is possible.

Internet of Things and Analytics

Gartner predicts that by 2020 there will be 25 billion Internet-connected things that will produce close to $2 trillion of economic benefit globally. Such a sizeable impact deserves a mention, especially since the value of connecting something to the Internet is to have the data generated by the connected unit consistently analyzed.

From an enterprise perspective, the leading verticals utilizing Internet of Things (IoT) are manufacturing and utilities. In 2015, it was estimated that the manufacturing sector has close to 307 million units considered IoT and the utilities sector had about 300 million IoT units. The retail sector is not far behind.

The IoT is actually the enabler of the Internet of Everything. These are not interchangeable concepts. While the IoT is units connected to the Internet, whether those units are cars, smart meters, or manufacturing sensors, the Internet of Everything (IoE) is the technology connection. The IoE provides the security, software-defined networking, unified communications, analytics, application-aware networking, database federation and mobile experience. The digitization of the enterprise is the foundation for IoE which is why digitization is so important for companies to stay competitive.

Fourth Industrial Revolution

Just as steam and mechanical production changed the world in the First Industry Revolution, then electricity and mass production changed it again in the Second Industrial Revolution, and IT and automated production changed it again in the Third Industrial Revolution, continuing to technologically innovate is again changing the world. As we continue to innovate—continue to improve technology—changing the world becomes not only more noticeable but also more realistic.

When we talk about the Fourth Industrial Revolution, the World Economic Forum describes it as: a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. What we’re talking about is the power of technology to change how we interact with each other, how we interact with objects, how objects interact with each other, how we work, how we play, how we grow as individuals and as a civilization. Answering how is the role of analytics.

The improvements we’re making with technology are very focused on making everything and everyone smarter. To become smarter requires ongoing analysis inside the technology itself and outside the technology constantly examining the environment around it, how we interact with it and react to it.

Why is analytics the new in-crowd? The ability to apply analytics to anything and everything in the enterprise is at the core of the Fourth Industrial Revolution. Analytics is now at a point where it can be the brain of the enterprise which is why it needs to be thought of separately, as its own application. Analytics allows human beings to be smarter, act faster, evolve and grow. Analytics is something that can be controlled to automatically make everything around us better.

Getting there is a journey. Like every journey the outcome is better with a destination in mind—getting stakeholders what they want when they want it. For a number of reasons described above, analytics has a very important role in enabling business to progress, compete and succeed. Whether you are a Bayesian or a connectionist—though both equally important and interesting–what matters most when investing in analytics is first to understand your business, its needs and its challenges.

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