The Top Technology Trends For The Next Three Years (Part 2)

As promised in my blog last week, here is part 2. In part 1, I introduced the two trends reports we did this year and showed the list of trends for business technology. These are trends and technologies to consider first with your "business hat" on. This blog post lists the other 10 trends to view first from a technology lens because they are of lower interest or impact to the business.

We have created four new categories to make IT stakeholder identification easier: 1) application platforms will be of high interest to your app dev and management teams; 2) integration will be of interest to app dev, data integration specialists, and even process folks (considering that processes can and should be integrated with apps and data); 3) infrastructure and operations; and 4) mobile computing, which spans infrastructure, app dev, and possibly line-of-business relationship managers who are very keen on mobility. And don't forget your security and compliance stakeholders, who will generally care about all of these!

Before listing the trends and technologies, I also want to introduce a new twist to our research this year - we have identified four major themes that run through many of our business technology and technology trends. These themes are so broad and far reaching that we thought it worth calling them out separately; we are advising our clients to understand these themes as the context for responding to individual trends:

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The Top Technology Trends For The Next Three Years

We just released our 2011 update to last year’s EA top trends report, The Top 15 Technology Trends EA Should Watch: 2011 To 2013. In 2011, we have expanded our coverage by releasing two documents of 10 trends each:

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Big Data Will Help Shape Your Market’s Next Big Winners

It seems that every week another vendor slaps “big data” into its marketing material – and it’s going to get worse. Should you look beyond the vendor hype and pay attention? Absolutely yes! Why? Because big data has the potential to shape your market’s next winners and losers.

At Forrester, we think clients must develop an intuitive understanding of big data by learning: 1) what is new about it; 2) what it is; and 3) how it will influence their market.

What is new about big data? We estimate that firms effectively utilize less than 5% of available data. Why so little? The rest is simply too expensive to deal with. Big data is new because it lets firms affordably dip into that other 95%. If two companies use data with the same effectiveness but one can handle 15% of available data and one is stuck at 5%, who do you think will win? The deal, however, is that big data is not like your traditional BI tools; it will require new processes and may totally redefine your approach to data governance.

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Big Data, Brewer, And A Couple Of Webinars

Whenever I think about big data, I can't help but think of beer – I have Dr. Eric Brewer to thank for that. Let me explain.

I've been doing a lot of big data inquiries and advisory consulting recently. For the most part, folks are just trying to figure out what it is. As I said in a previous post, the name is a misnomer – it is not just about big volume. In my upcoming report for CIOs, Expand Your Digital Horizon With Big Data, Boris Evelson and I present a definition of big data:

Big data: techniques and technologies that make handling data at extreme scale economical.

You may be less than impressed with the overly simplistic definition, but there is more than meets the eye. In the figure, Boris and I illustrate the four V's of extreme scale:

The point of this graphic is that if you just have high volume or velocity, then big data may not be appropriate. As characteristics accumulate, however, big data becomes attractive by way of cost. The two main drivers are volume and velocity, while variety and variability shift the curve. In other words, extreme scale is more economical, and more economical means more people do it, leading to more solutions, etc.

So what does this have to do with beer? I've given my four V's spiel to lots of people, but a few aren't satisfied, so I've been resorting to the CAP Theorem, which Dr. Brewer presented at conference back in 2000. I'll let you read the link for the details, but the theorem (proven by MIT) goes something like this:

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Do Not Depend On EA To Innovate

Many organizations expect EAs to be the source of technology innovations. They are broadly knowledgeable, experienced, connect-the-dots kind of people you might naturally expect to come up with reasonable ideas for new approaches and technology. When you think about it a bit, this expectation is misplaced. Here’s why I think this:

The best technology innovators are users who have a problem to solve; motivation to solve a specific problem affecting their lives is the key ingredient. EAs just don’t have these kinds of problems; because they operate as a bridge between business and technology, most often they are attempting to solve things that affect other people’s lives. Please don’t get me wrong: EAs are always looking for new, innovative ways to improve things. But this doesn’t replace the “I gotta fix this now” kind of motivation inspiring most innovations.

So am I saying organizations should take EAs out of the innovator role? Yes and no.

Here at Forrester, we have been writing and talking about topics such as Innovation Networks and new roles for business technology for a while. I think that EAs are better placed at the center of an Innovation Network where they connect innovation suppliers (lead users who are dreaming up new ways to solve their problems) with innovation users (other folks who can benefit from a generalization of the solutions the suppliers come up with). In addition, EAs can bring innovation implementers — the team members who know how to actually make innovations into solutions that work for more than just one individual or group — into the conversation.

So what should you do?

  1. Send EAs on a mission to find people doing innovative things in IT and the business. This has a side effect of connecting EAs to the frontlines, where they might discover all kinds of things.
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Please Join Us At The Forrester Technology Trends Tweet Jam, 10-11 ET on 7/29

It's that time again, and we are busy updating our annual report, "The Top 15 Trends EA Should Watch." For this year, we have expanded the number of analysts contributing to the research, and we want to capture your thoughts condensed into 140 character sound bytes.

In addition to using the jam as research, we are going to prepare a second, special report citing key tweets and providing our analysis. We will make this report available on request to non-clients who participate, so come join us!

Info on the Jam

  • Hash tag: #forrtttj
  • When: Friday, 7/29, 10-11 a.m. Eastern time
  • Host: Brian Hopkins (@practicingEA)

Scope of the jam:

We predicted that 2011 would be about mobile, social, cloud and data. So far we have been right, but things are always changing. Some things we want to jam on:

  • What are the major technology landscape shifts you are seeing?
  • Are social, mobile, cloud and data still the big four or are there new things going on? What about each of these is interesting or vexing? What are the key shifts in client and vendor approaches?
  • What technologies are looming big on your radar this year and next?
  • Around the halfway point I'll steer the jam towards speculation -- what's going to happen that we don't expect?
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Spiders And Elephants – Social Connections And Big Data Will Determine The Next Big Winners And Losers

I’ve been following a couple of 2011 developments that together may determine the next big technology winners and losers. To get your click, I’ve been obscure in my title.

Spiders refers to the battle for control of the webs that connect us all together. Google won the first race by connecting webs of content, and now the second race is on for control of the social web. Facebook dominates the personal market, while LinkedIn has carved out a niche with professionals and now challenges its big cousin. Finally, latecomer Google (anybody see the irony?) may just sneak up on both by capitalizing on their respective weaknesses.

So what?

Consider this: The winner will control the web of social data. What people like, who they know who likes similar stuff, and where these potential customers are. This is powerful stuff that companies are just beginning to figure out. For example, a mobile app identifies five people in your condo complex who are big scuba divers, and one is on the boat trip with you right now. By helping you make connnections, the app’s developer can now sell marketing data to dive boat charters that then can offer you a group discount to come back together with your other new connections. Clearly, the company in control of this data will be in the center of a market worth a mind-blowing amount of money.

Elephants is an allusion to Hadoop and Horton, two pachyderms that represent that growing interest in big data technology. Eric Baldeschwieler, former Hadoop project leader at Yahoo and now CEO of Hortonworks, went so far as to state, “. . . We anticipate that within five years, more than half the world's data will be stored in Apache Hadoop.”

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Enterprise Data Management Is Not The Holy Grail

From my first days as a baby architect, I was spoon-fed the idea that enterprise data management (EDM) was the solution to our data woes. Some call it enterprise information management or other names that mean a holistic approach to managing data that is business led and centered on stewardship and governance. The DMBOK provides a picture that describes this concept very well — check it out.

Here’s the problem: Most firms are not able to internalize this notion and act accordingly. There are myriad reasons why this is so, and we can all list off a bunch of them if we put our minds to it. Top of my list is that the lure of optimizing for next quarter often outweighs next year’s potential benefits.

Here’s another problem: Most EAs cannot do much about this. We are long-term, strategic people who can clearly see the benefits of EDM, which may lead us to spend a lot of time promoting the virtues of this approach. As a result, we get bloody bruises on our heads and waste time that could be spent doing more-productive things.

I do think that taking a long-term, holistic approach is the best thing to do; in my recently published report "Big Opportunities In Big Data," I encourage readers to maintain this attitude when considering data at extreme scale. We need to pursue short-term fixes as well. Let me go a step further and say that making short-term progress on nagging data management issues with solutions that take months not years is more important to our firms than being the EDM town crier. Hopefully my rationale is clear: We can be more effective this way as long as our recommendations keep the strategic in mind.

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What Happens When Central "IT" No Longer Exists?

When we get used to something, we often think it will never change, but it does eventually; who bought a house in 2006 and assumed the value would surely keep going up?

We are working at an architectural inflection point. The signals are all around us – cloud, big data, mobility, smart computing, etc. While each of these appears to be only modestly connected, I think together they signify a major shift in how business gets done and in the architecture that supports it. If true, this means the tried-and-true Business-Data-Applications-Technology model architected and delivered by central IT will not serve us much longer.

Consider the following:

  • Big and complex are here to stay. In the past we strove for simplicity because we did not have the techniques and technology to deal with the world as it is – infinitely complex. Read Chaos: Making a New Science by James Gleick. The cloud has brought the power of distributed, elastic computing to bear on enormous problems, and this trend will continue. Will central IT continue to grow in response to the increasing size and complexity of technology problems, or will a different model arise?
  • The cloud and the App Internet are two sides of the same coin. The cloud is about optimizing the power of centralized data processing, while the App Internet is about exploiting the enormous power of mobile devices on the periphery. What happens when we figure out how these work together? Can we create a smart grid across mobile devices that also leverages cloud resources? What can we accomplish when apps no longer live in central data centers that we own and control?
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Is Moore's Law Still Valid?

Has anybody noticed that processor speed has stopped doubling every 18 months? This occurred to me the other day, so I took some time to figure out why and draw some conclusions about Moore's law and the impacts of continued advances in chip technology. Here what I've come up with: 1) Moore's law is still valid, but the way processor power is measured has changed, 2) disk-based memory is going the way of the cassette tape, and 3) applications will move into the cloud.

We have pushed semiconductor technology to its physical limits, including our ability to cool chips and the speed of light. As a result, chip manufacturers have turned to multicore processing technology rather than pure chip and bus speed. Now the power of a microprocessor is judged by the number of cores it contains — and the number of cores on a single chip will continue to increase for the near future.

So what? Extra cores per chip means more parallel processing to speed through operations — so parallel is the future.

Two other trends are also important to understand my conclusions:

  1. RAM keeps getting more powerful and cheaper.
  2. As the number of cores in a chip goes up, its ability to process data begins to exceed bus technology’s ability to deliver it. Bus speed is governed by Moore’s law.
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