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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Customer Journey Analytics vs. Traditional Analytics—Know the Difference

It’s expected that 60% of all large organizations will develop customer journey mapping capabilities by 2018. Why? Because the average consumer isn’t so average anymore. Consider that a typical customer now owns three personal mobile devices, each with anywhere from 10 to 20 downloaded apps. This individual owns an average of five social media accounts, nearly three of which are actively used. Additionally, the average office worker receives up to 121 personal emails per day. Just imagine what these figures look like for consumers on the high end of this engagement spectrum.

To get a snapshot of my own activity, I followed these simple instructions to figure out how many emails I receive. It’s 10 a.m. and I show 59 emails received (up from 47 just two minutes ago). And tweets average around 6,000 per second—I have 1,175 in my queue based on who I am currently following. The question is: How do you bring your email, tweet, post, or blog to my attention amid all the clutter?

When we look at what this means to customer experience it is worth noting that we’ve reached a point where over 40% of customers now use up to seven different channels to interact with brands, from live chat to email to social media to SMS. Businesses increasingly understand this fact, and they’re taking the necessary steps to ensure they can deliver consistent, contextualized experiences across various channels and devices.

Each of the devices and channels offers its own set of diverse scenarios for linking to other devices and channels, making no two customer experiences the same. The not-so-good news is that businesses are still grappling to understand customers’ actions across these various touchpoints. They need to leverage data but, in fact, 43% of companies currently obtain little tangible benefit from their data, while 23% admit they derive no benefit whatsoever. Organizations are struggling to create a data strategy that delivers the insights needed to drive anticipatory engagement and repeat spending.

The bottom line is that a business can support virtually every interaction channel. However, without a comprehensive view of the data generated and shared across those channels organization-wide, it will fail. Supporting an array of channels is simply not enough. Businesses must gain an inherent understanding of how customers are using these channels so that they can adapt, evolve and change as needed. This is where the ability to understand your data—specifically, customer journey analytics—becomes vital.

The solution here may be simple to describe, but implementing it isn’t. Adopting customer journey analytics means businesses must now support a powerful, real-time visualization of the customer journey across all lines of business, not just the contact center. They need a roadmap to continually reinvent key processes and fine-tune organizational behavior. They must harness real-time and historical data across all channels and devices to intuitively understand customer needs and optimize business outcomes. Most challenging of all, they must do this in a way that shows tangible ROI and improves TCO.

To make customer journey analytics work, businesses must take a critical step from ideology to implementation—a move that can often feel like a leap of faith.

But there’s good news: technology has evolved to a point where companies can now easily, effectively and cost-efficiently achieve these core data objectives. The key is investing in an extensible, omnichannel customer engagement solution.

Your customer engagement solution should boast simple capabilities. It should be pretty easy to create and manage dynamic, multi-touch customer journeys. And you need a built-in, flexible analytics and reporting platform to deliver a single, comprehensive view of customer data across all sources, both internal and external. This lets you compete using customer journey analytics, and also easily add third-party data sources to amplify their strategy.

A customer engagement platform redefines the way businesses engage with digital consumers. Here’s how customer journey analytics stand apart from traditional reporting and analytics:

  • Obliterates Siloes: A siloed environment is the greatest barrier to data success, and it’s affecting more businesses than we realize. According to Deloitte’s 2017 “Contact Center Benchmarking Report,” nearly 60% of customer channels are currently being managed in silos. Analytics integration is vital for competing on customer experience (CX), an initiative that traditional analytics tools simply can’t support.

    Built on open, extensible architecture, a customer engagement platform has unparalleled flexibility for gathering transactional information from numerous different channels (IM, co-browsing, SMS, phone, email, IoT) and devices (phone, mobile/tablets, branch, desktop, kiosks). This enables companies to flexibly collect, process and analyze all real-time and historical data. They gain a rich visualization of their customer journey enterprise-wide. This means consistent, contextualized experiences no matter where and when interactions begin, end, continue—and no matter how many company agents are communicating with the customer.

  • Seamlessly combines internal and external data sources: The open nature of a customer engagement platform enables companies to combine internal data with that of virtually any other business intelligence (BI) tool. For example, insights collected internally can be combined with data from visualization tools from leading providers like MicroStrategy, Oracle, SAP and Tableau. This lets managers maximize the return on their existing investments, while driving their potential beyond what was initially imagined.

    Furthermore, this unique ability lets managers generate cradle-to-grave customer interaction reports, enabling them to identify innovative new ways to meet consumers’ evolving needs. Chances are you’re not going to get this with traditional reporting and analytics platforms.

  • Transforms the agent experience: A holistic customer engagement platform redefines agent and supervisor experiences by allowing companies to easily create, customize and integrate key applications for specific work groups. Supported by an advanced software development kit, companies can build their own contact center apps, or embed specific functions into their existing apps, to customize desktops for any unique customer/agent configuration. The solution represents a revolutionary way to serve digital consumers. And, it offers managers a new avenue for analyzing performance metrics for all ways customers are served.

With customers using more digital channels than ever, it’s clear that now is the time to adopt customer journey analytics via a customer engagement platform.

Interested in learning more or chatting about transforming your analytics environment? Contact us. We’re here to help and would love to hear from you.

Next-Generation IT: What Does It Really Look Like?

From mainframes to virtualization to the IoT, we’ve come a long way in a very short amount of time in terms of networking, OS and applications. All this progress has led us to an inflection point of digital business innovation; a critical time in history where, as Gartner puts it best, enterprises must “recognize, prioritize and respond at the speed of digital change.” Despite this, however, many businesses still rely on legacy systems that prevent them from growing and thriving. So, what’s the deal?

I attempted to answer this in a previous blog, where I laid out as entirely as I could the evolution of interconnectivity leading up to today. What was ultimately concluded in that blog is that we have reached a point where we can finally eliminate dependency on legacy hardware and hierarchical architecture with the use of one single, next-generation software platform. The call for organizations across all industries to migrate from legacy hardware has never been stronger, and the good news is that technology has evolved to a point where they can now effectively do so.

This concept of a “next-generation platform,” however, isn’t as simple as it sounds. Just consider its many variations among industry analysts. McKinsey & Company, for example, refers to this kind of platform as “next-generation infrastructure” (NGI). Gartner, meanwhile, describes it as the “New Digital Platform.” We’re seeing market leaders emphasizing the importance of investing in a next-generation platform, yet many businesses still wonder what the technology actually looks like.

To help make it clearer, Avaya took a comparative look at top analyst definitions and broke them down into five key areas of focus for businesses industry-wide: 

  1. Next-generation IT
  2. The Internet of Things (IoT)
  3. Artificial intelligence (AI)/automation
  4. Open ecosystem
  5. The customer/citizens experience

In a series of upcoming blogs, I’ll be walking through these five pillars of a next-generation platform, outlining what they mean and how they affect businesses across every sector. So, let’s get started with the first of these: next-generation IT.

Simplifying Next-Gen IT

As IT leaders face unrelenting pressure to elevate their infrastructure, next-generation IT has emerged as a way to enable advanced new capabilities and support ever-growing business needs. But what does it consist of? Well, many things. The way we see it, however, next-generation IT is defined by four core elements: secure mobility, any-cloud deployment (more software), omnichannel and big data analytics—all of which are supported by a next-generation platform built on open communications architecture.

Secure mobility: Most digital growth today stems from mobile usage. Just consider that mobile now represents 65% of all digital media time, with the majority of traffic for over 75% of digital content—health information, news, retail, sports—coming from mobile devices. Without question, the ability to deliver a secure mobile customer/citizen experience must be part of every organizational DNA. This means enabling customers to securely consume mobile services anytime, anywhere and however desired with no physical connectivity limitations. Whether they’re on a corporate campus connected to a dedicated WLAN, at Starbucks connected to a Wi-Fi hotspot, or on the road paired to a Bluetooth device though cellular connectivity, the connection must always be seamless and secure. Businesses must start intelligently combining carrier wireless technology with next-generation Wi-Fi infrastructure to make service consumption more secure and mobile-minded with seamless hand-off between the two technologies.

Any-cloud deployment: Consumers should be able to seamlessly deploy any application or service as part of any cloud deployment model (hybrid, public or private). To enable this, businesses must sufficiently meet today’s requirements for any-to-any communication. As I discussed in my previous blog, the days of nodal configuration and virtualization are a thing of the past; any-to-any communications have won the battle. A next-generation platform built on open communications architecture is integrated, agile, and future-proof enough to effectively and securely support a services-based ecosystem. Of course, the transition towards software services is highly desirable but remember not all hardware will disappear—although where possible it should definitely be considered. This services-based design is the underlying force of many of today’s greatest digital developments (smart cars, smart cities). It’s what allows organizations across every sector to deliver the most value possible to end-users.

Omnichannel: All communication and/or collaboration platforms must be omnichannel enabled. This is not to be confused with multi-channel. Whereas the latter represents a siloed, metric-driven approach to service, the former is inherently designed to provide a 360-degree customer view, supporting the foundation of true engagement. An omnichannel approach also supports businesses with the contextual and situational awareness needed to drive anticipatory engagement at the individual account level. This means knowing that a customer has been on your website for the last 15 minutes looking at a specific product of yours, which they inquired about during a live chat session with an agent two weeks ago. This kind of contextual data needs to be brought into the picture to add value and enhance the experience of whom you service, regardless of where the interaction first started.

Big data analytics: It’s imperative that you strategically use the contextual data within your organization to compete based on the CX. A huge part of next-generation IT involves seamlessly leveraging multiple databases and analytics capabilities to transform business outcomes (and ultimately, customers’ lives). This means finally breaking siloes to tap into the explosive amount of data—structured and unstructured, historical and real-time—at your disposal. Just as importantly, this means employees being able to openly share, track, and collect data across various teams, processes, and customer touch points. This level of data visibility means a hotel being able to see that a guest’s flight got delayed, enabling the on-duty manager to let that customer know that his or her reservation will be held. It means a bank being able to push out money management tips to a customer after seeing that the individual’s last five interactions were related to account spending.

These four components are critical to next-generation IT as part of a next-generation digital platform. Organizations must start looking at each of these components if they wish to compete based on the CX and respond at the speed of digital change. Stay tuned, next we’ll be talking about the ever-growing Internet of Things!

Avaya Predictions for 2017 Services Trends: Top Focus is on Smart Customer-Centric Engagement

Recently, we asked six Avaya services experts to help us reflect on the past year and to peer ahead into 2017. Our panel:

  • Richard English, Managing Director, Avaya Professional Services
  • Camille Lewis, Product Management Director, Avaya Client Services
  • Barbara Sidari, Customer Engagement and Executive Cadence, Avaya Client Services
  • Thomas Brennan, Vice President of global support services, private cloud and managed services delivery
  • Michael Sale, Director Online Engagement, Avaya Client Services
  • Dan Pratt, Senior Director, Business Transformation and Strategy, Avaya Client Services

According to our six experts, our predictions for these 2016 trends proved to be spot on—and they will continue to be a force in 2017:

  • Use of hybrid/private cloud

    will continue to dominate for large enterprises until public cloud providers can demonstrate that compliance to privacy/security regulations such as HIPAA can be achieved. However, Public Cloud is quickly becoming a flexible and effective delivery model for the midmarket.

  • A flexible delivery model

    to achieve growth in modular steps that helps IT maximize ROI and support rapid business scaling has been, and will continue to be, extremely successful. Taking some of the burden off the enterprise enables IT managers to focus on more strategic corporate initiatives.

  • The need for person-to-person human touch

    will continue to rise. It will become critical in 2017 as unassisted support and self-healing systems grow smarter in identifying trends and problems before they happen and engage in machine-to-machine maintenance for resolution. The use of video will be more widely used, providing personalization and higher customer satisfaction.

The panel thinks that 2017 will mean an increasing focus on smart customer centric engagement when it comes to service. In 2017, it’s all about using analytics and even smarter technology to increase customer satisfaction (CSAT) scores, loyalty and revenue—and to achieve a better return on investment.

The Avaya panel sees these three trends emerging in 2017:

  • Transforming legacy systems and increased customer use of omnichannel will streamline the customer journey to increase customer satisfaction, loyalty and revenue.

    For example, many retailers will transform their Contact Centers into profit centers. The shopping experience for their customers starts on the mobile device or web-based applications—retailers want it to end with an order placed. The customer will experience a seamless transition from mobile to voice (or to web chat or video) without having to repeat who they are and what they want to purchase. The agent will already know the value of the customer to their company and will provide a personalized shopping experience.

  • Analytics, Internet of Things (IoT), and big data will enhance the experience of the Customer Journey.

    The predictive and preemptive active workflow will match people to people, machine to machine, as preferred by the customer for maximum satisfaction and profit. For instance, service vendors will use data captured from customer service requests, alarms, outage history, and project volume to identify risks and take appropriate actions to proactively mitigate issues. Utility companies can leverage web-based applications to proactively communicate to customers the status of affected service areas via maps on smart phones, reducing the burden of customers calling the service center to report an outage. Similarly alarm companies will analyze alarms and preemptively fix them before the consumer arrives home.

  • Demand for holistic application service management will grow as siloed and disparate cloud applications shift focus from managing assets in the field to delivering on business processes.

    Enterprises will need a dashboard that provides a single pane view by business process vs CPU performance. The workforce needs to be trained to leverage all the data in a way that includes human touch.

The year 2017 promises to be very exciting as service transforms and demonstrates its value by preemptively fixing issues before they become problems. It is imperative that knowing the customer and providing what they want, as well as the human touch, will become ever more critical in a big data world. After all, it’s all about the customer experience!

What do you see emerging in 2017? Drop me a note at sithomso@avaya.com