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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A Travel Nightmare: How To Ignore Data, Remain Clueless, And Anger Your Customers

Firms are blowing opportunities to engender their customers’ lifelong loyalty. Here’s an example from my own recent experience:

As an analyst, I fly 100,000-plus miles with a preferred airline every year, and I’m a mobile mind-shifted consumer; therefore, I have made some assumptions that have led to an expectation. Assumption — weather delays are not a new phenomenon in travel; assumption — the technology to analyze data and communicate with passengers has been around for a while now, and my big airline that is bleeding money out of its ears should have invested in it; expectation — my airline is going to use my mobile device to understand and take care of me because I’m important to them.

Here’s a summary of how that turned out not to be the case and how my airline could have used systems of insight to handle a bad situation and secure my lifetime loyalty:

Data they had access to: Weather projections over Chicago.

  • Insight they should have had: My aircraft had a high probability of flying right into a bad system.
  • Action they could have taken: They could have rebooked me before I got on the plane.
  • What actually happened: I was stranded in Chicago when a tornado touched down at about the same time I did.
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Systems Of Insight Will Power Digital Business

In digital business analytics, only delivering insight at the point of action matters. Did your customer get the right information, in context, at her moment of need? Did your firm use that engagement to make the right offer and up sell? Do your sales or call center reps have the insight they need to set priorities or meet customers needs efficiently? Talk of big data, advanced analytics, and agile BI is all about turning data into insight. But that is only part of the solution. How is your firm systematically testing insights and finding those that matter? How are you embedding insights in the software that your customers and employees use to engage? Are you even thinking about how to tap all the data that results from that engagement to find out what worked and what didn’t?

If you are not addressing all of these holistically, then Hadoop and that shiny new predictive analytics or streaming tool that sit on it are going to leave your business wanting. Don’t get caught in the trap.

My colleague Ted Schadler and I spent a year researching what it really takes to be successful; we found many companies drowning in data and starving for insight that made a difference. But a few leaders were working at the beginnings of closed loop systems to: 1) discover the insights that matter most; 2) embed them into the software their customers and employees use to engage; and 3) continuously measure and learn from the results.

We call these “systems of insight” and believe they will be the engines that power the digital business of the future.

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Big Data, Welcome To Those Awkward Teenage Years

Just a few years ago, when big data was associated primarily with Hadoop, it was like a precocious child…fun for adults, but nobody took it seriously. I’m attending Strata in San Jose this February, and I can see things have changed. Attendance doubled from last year and many of the attendees are the business casual managers – not the blue jeaned developers and admins of days gone by. Big data is maturing and nobody takes it lightly anymore.

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Is Big Data Enough? (Ramping Up For Strata In San Jose)

I’m ramping up to attend Strata in San Jose, February 18, 19 and 20th. Here is some info to help everyone who wants to connect and share thoughts. Looking forward to great sessions and a lot of thought leadership.

I’ll be setting aside some time for 1:1 meetings (Booked Full)

[Updated on 2/17] - I have set up some blocks of time to meet with people at Strata. Please follow the link below to schedule with me on a first come basis.

[Update] - I booked out inside 2 hours...didn't expect that! I may open up my calendar for more meetings but need to get a better bead on the sessions I want to attend first. Shoot to catch me at breakfast, will tweet out when I'm there.

I’ll be posting my thoughts and locations on Twitter

The best way to connect with me at Strata is to follow me on Twitter @practicingea

You can post @ me or DM me. I’ll be posting my location and you can drop by for ad hoc conversations as well.

I’m very interested in your point of view - data driven to insights driven

I am concluding very quickly that “big data” as we have viewed it for the last five years is not enough. I see firms using words like “real-time” or “right-time” or “fast data” to suggest the need is much bigger than big data – its about connecting data to action in a continuous learning loop.

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Elephants, Pigs, Rhinos and Giraphs; Oh My! – It's Time To Get A Handle On Hadoop

By now you have at least seen the cute little elephant logo or you may have spent serious time with the basic components of Hadoop like HDFS, MapReduce, Hive, Pig and most recently YARN. But do you have a handle on Kafka, Rhino, Sentry, Impala, Oozie, Spark, Storm, Tez… Giraph? Do you need a Zookeeper? Apache has one of those too! For example, the latest version of Hortonworks Data Platform has over 20 Apache packages and reflects the chaos of the open source ecosystem. Cloudera, MapR, Pivotal, Microsoft and IBM all have their own products and open source additions while supporting various combinations of the Apache projects.

After hearing the confusion between Spark and Hadoop one too many times, I was inspired to write a report, The Hadoop Ecosystem Overview, Q4 2104. For those that have day jobs that don’t include constantly tracking Hadoop evolution, I dove in and worked with Hadoop vendors and trusted consultants to create a framework. We divided the complex Hadoop ecosystem into a core set of tools that all work closely with data stored in Hadoop File System and extended group of components that leverage but do not require it.

In the past, enterprise architects could afford to think big picture and that meant treating Hadoop as a single package of tools. Not any more – you need to understand the details to keep up in the age of the customer. Use our framework to help, but please read the report if you can as I include a lot more there.

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Forrester's Top Emerging Technologies To Watch, Now Through 2020

Technology has given your customers choices and digital predators the edge. Ask marketing, they will tell you about the decreasing effectiveness of traditional campaigns. Look at your business strategy and find plans to address new digital competitors that have become serious threats overnight. Across the board, Forrester finds high expectations that emerging technology will help firms stay competitive amidst these changes. But which ones should you pay attention to? Cloud, mobile, social, Read more

How Do New “Systems Of Insight” Power Great Mobile Moments And Customer Experiences?

Customers crave contextual and personal experiences on their mobile devices. Companies are looking to the reams of location and behavior data spun off mobile device to deliver them. Meanwhile, executives long for the insights lurking just below the surface of the new data they collect on customers and prospects to improve services and chart the best business strategy. 
In most companies, mobile engagement, customer analytics, innovation, and business strategy happen in silos and often half-heartedly. But disrupters like Uber, TripIt, Netflix, Flipboard, and Starbucks deliver great and personalized mobile and digital experiences -- and optimize outcomes -- with insights derived from all the data they can gather.
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