Forrester's Top Emerging Technologies To Watch: 2017-2021

Think back just a few years — social, mobile, cloud, and big data ruled the emerging technology landscape. Business and technology management executives wondered what big data meant, when the cloud would disrupt their companies, and how to engage effectively on social channels. In 2016, Hadoop turned 10, the cloud has been around even longer, and social has become a way of business and life. So what’s next?

 

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Tame The Beast: Forrester's Insight Platform Vendor Landscape

The mix of analysts who showed up to a recent Cambridge Semantics briefing illustrates a big problem data and analytics technology buyers have - too many data and analytics solutions and a ton of overlap. For example, of the five analysts who came:

  • One saw Cambridge Semantics as a text analytics tool — and that is true.

  • Another saw it as a search tool — and that too is true.

  • A third viewed it as a cognitive analytics tool — and that is true as well.

  • A fourth came because it was a "BI" tool . . . see my point?

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Insights-Driven Businesses Are Stealing Your Customers

Is your business digital? Like Domino’s Pizza, do you realize that you are not a product or service business, rather you are a software and data business that provides products or services? Do you exploit all of your customers' data to know them inside-out? Are customers flocking to you because you are driving every engagement with insight about them? If the answer to any of these questions is not a resounding, “Yes!”, then you are losing revenue and shareholder value.

In Forrester’s new report, The Insight Driven Business, my colleagues Ted Schadler, James McCormick and I identify a type of business that ignores the "data driven" hype. Instead, insights-driven businesses focus on implementing insights - that is actionable knowledge in the context of a process or decision - in the software that drives every aspect of their business. This is a big shift from most firms that fret over big data and technology. Instead insights-driven businesses focus on turning insights into action. The big data and technology pieces come along naturally as a consequence.

To gauge the economic impact of insights-driven businesses, Forrester built a revenue model that conservatively forecasts insights-driven businesses will earn about $400 billion in 2016; however, by 2020 they will be making over $1.2 trillion a year due to an astonishing compound annual growth rate between 27% and 40%. Given that global growth is less than 4%, how will they pull this off? Plain and simple, they’ll do this by understanding customers more deeply and using that insight to steal them from their competition. 

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Insight Platforms Have Arrived

Are you lost in a confusing soup of vendor-speak about what their data analytics stack actually offers? Big data, data platforms, advanced analytics, data lakes, real-time everything, streaming, the IoT, customer analytics, digital intelligence, real-time interaction, customer decision hubs, new-stuff-as-a-service, the list goes on.

Recognize the convergence happening as vendors evolve their technologies from doing just one thing like predictive analytics or search to many things together. For example, data integration, data warehouse, and BI tools are typically sold separately, but breakout vendor Looker combines data integration, model governance, basic BI, and a runtime for data applications all in one software layer that sits on your data lake. As another example, consider predictive analytics vendor Alpine Data Labs or SAS Viya from SAS. These vendors have built out a lot of data management and insight delivery tooling into their platforms because without it users struggle to maximize value. Another trend is big data search vendors like Maana that now also include hooks for predictive model execution as well as more data management functions. Lastly, systems integrators are packaging their IP and offering it as a data management and analytics integrated product — for example, Saama’s Fluid Analytics Engine or Infosys’ Information Platform.

In fact, the list of innovative vendors blending data management, analytics, and insight execution technology is growing by leaps and bounds. To address this trend, I just published a report, Insight Platforms Accelerate Digital Transformation, in which I created a broad definition that labels this trend:

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Think You Want To Be "Data-Driven"? Insight Is The New Data

It’s been a while since I’ve blogged; not because I’ve had nothing to say, but rather because I’ve been busy with my colleagues Ted Schadler, James McCormick, and Holger Kisker working on a new line of research. We wanted to examine the fact that business satisfaction with analytics went down 21% between 2014 and 2015, despite big investments in big data. We found that while 74% of firms say they want to be “data-driven,” only 29% say they are good at connecting analytics to action. That is the problem.

Ted Schadler and I published some initial ideas around this idea in Digital Insights Are The New Currency Of Business in 2015. In that report, we started using the phrase digital insight to talk about what firms were really after ― action inspired by new knowledge. We saw that data and analytics were only means to that end. We also found that leading firms were turning data into insight and action by building systems of insight ― the business discipline and technology to harness insights and consistently turn data into action.

Here is a key figure from that report:

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Forrester’s 2016 Predictions: Turn Data Into Insight And Action

Three of four architects strive to make their firms data driven. But well-meaning technology managers only deal with part of the problem: How to use technology to glean deeper, faster insight from more data -- and more cheaply. But consider that only 29% of architects say their firms are good at connecting analytics results to business outcome. This is a huge gap! And the problem is the ‘data driven’ mentality that never fights it’s way out of technology and to what firms care about - outcomes.

In 2016, customer-obsessed leaders will leapfrog their competition, and we will see a shift as firms seek to grow revenue and transform customer experiences. Insight will become a key competitive weapon, as firms move beyond big data and solve problems with data driven thinking.

Shift #1 - Data and analytics energy will continue drive incremental improvement

In 2016, the energy around data-driven investments will continue to elevate the importance of data and create incremental improvement in business performance. In 2016, Forrester predicts:

  • Chief data officers will gain power, prestige and presence...for now.  But the long term viability of the role is unclear. Certain types of businesses, like digital natives, won’t benefit from appointing a CDO.
  • Machine learning will reduce the insight killer - time. Machine learning will  replace manual data wrangling and data governance dirty work. The freeing up of time will accelerate data strategies.
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IBM And Teradata — A Tale Of Two Vendors’ Struggle With Disruption

I said that 2015 would be a tough year for enterprise data and analytics vendors in my spring report, "Brief: Turning Big Data Into Business Insights, 2015." I thought two things would happen. First, open source would drag on vendors’ revenues as demand for big expensive products declined. Second, the cloud would create revenue headaches. Turns out, I was right. Teradata's midyear earnings were down 8%, and IBM reported that Q2 revenue was down 12% from a year ago. As further proof, consider the rash of data management vendors running for private equity (e.g. Dell/EMC, Informatica, and TIBCO). It’s been tough times indeed, even though most vendors are keeping their messaging positive to reassure buyers and investors.

Over the past two weeks, I attended Teradata Partners in Anaheim and IBM Insight in Las Vegas — giving me a firsthand look at how two giants of the data and analytics industry are handling disruption. What I saw was a tale of two vendors that couldn’t be any more different:

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The Top Technology Trends To Watch: 2016 To 2018

Enterprise architects face more exciting — and greater — challenges as the age of the customer takes off. But technology invention, innovation, and spending are notoriously cyclical. In fact, our first tech trends report in 2009 predicted a boom cycle through 2016. And we have seen this — with social, mobile, cloud, analytics, and big data, to name just the obvious ones. A big finding of our research however is this: The Age Of The Customer has changed the classic technology investment cycle.  For example, technology management’s spend will grow about 5% in North America in 2016. This is a decent pace. However, spend on business technology — the things that let firms win, serve, and retain customers — will be double that!

All this new money will shift the focus of investment from point solution inventions toward “end-to-end innovation” by 2018. And by end-to-end, we mean across the customer life-cycle and customer journeys as opposed to classic 'enterprise integration'. This shift will happen in three phases:

  • Visionaries will dominate dawning phase trends as they drive point inventions to address specific business organizations’ opportunities.
  • Fast followers will discover the limits of point solutions in the awareness phase and begin to work through them.
  • Enterprises will shift investment toward integrating capabilities across the customer life cycle in the acceptance phase.
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Think A Data Lake Is THE Answer? Think Again. Here Comes Elastic Analytics

Enterprise architects, are you mired in a tangled web of data marts while your business pursues customer engagement without you? If you think a Hadoop-centric architecture is going to save the day, you may need to rethink. Your customers expect you to create systems of insight to deliver win-win engagement in real time. I'm seeing a new class of digital predators leverage the cloud to do just this. For example, Netflix designs cover graphics for its series based on subscriber viewing habits. They know their customers that well.

I call their technology approach an Elastic Analytics Platform in my recently published report. I formally define it as:

"A combination of data storage and middleware technology that allows the creation and dissolution of analytics components on demand, while provisioning these with data from one, or a few, distributed, virtualized data sources."

That's a mouthful. So here's a rough picture:

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“Big Data” Has Lost Its Zing – Businesses Want Insight And Action

I saw it coming last year. Big data isn’t what it used to be. Not because firms are disillusioned with the technology, but rather because the term is no longer helpful. With nearly two-thirds of firms having implemented or planning to implement some big data capability by the end of 2015, the wave has definitely hit. People have bought in.

But that doesn’t mean we find many firms extolling the benefits they should be seeing by now; even early adopters still have problems across the customer lifecycle. Can your firm understand customers as individuals, not segments? Are analytics driving consistent, insightful experiences across channels? Does all that customer insight developed by marketing make a bit of difference to your contact center agents? If you're like most firms, the answer is, “Not yet, but we're working on it.”

What’s more, firms expect that big data will deliver the goods. In fact, about three in four leaders tell us that they expect big data analytics to help improve and optimize customer experiences. That's a huge expectation!

I think big data is going to be a big letdown when it comes to customer engagement and experience optimization.

Here's why – big data is about turning more data into insight. In fact, our latest data and analytics survey tells me that big data plans are still overwhelmingly an IT department thing. As such, they have fallen victim to supply side thinking – just furnish the data and the technology, “the business” will do the rest. Really?

Big data will not help you:

  • Ensure insights are tested for value against business outcomes.
  • Deliver insights at the point of decision in software.
  • Close the loop between actions, digital reactions, and learning.
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