The Next Big Thing
Posts about next generation technologies and their effect on business.

Grading my predictions for 2014

grading predictions.pngEach year about this time I look back at the prediction post I made the previous year December (200620072008200920102011, 2012, 2013). I didn’t do predictions the first year I blogged but have managed to do one every year since.

 

Now it is time to look at 2014. I said that 2014 was going to be a year of instability. Depending on what industry sector or organization you’re in that was definitely true – but that’s the kind of easy prediction any fortune teller could make. Let’s get into the details:

 

I’ll grade myself with the following scale again this year:

A: Big changes during the year that are having wide effect.

B: Notable progress through the year and isolated areas of significant impact.

C: Progress with some impact

D: Little progress or impact – but work still taking place

F: No progress or the concept abandoned in any commercial sense.

 

Grade

Prediction

Rational

B

Shift from commodity services to a value play

This is definitely happening but slower than I thought it would.

C

Relationships shifting up the stack (from IaaS to Paas or SaaS to business services)

Although business-based outcomes are becoming common, there is still more smoke than fire here.

C

Similarly the view of BYOD will shift to more of a services perspective.

This one I also give myself mixed reviews. Although the BYOD momentum has shifted to more services, we are still not seeing real security brokerage services or other high value services in a standardized form.

A

New style of business

We have definitely seen much more discussion about the business capabilities and new needs provided by new computing capabilities. The concept of a race with the machine has definitely gained in mind share in 2014. Although the self-aware enterprise is still a long way off.

B

Wearables

I have mixed feelings on this rating. Although you can’t throw a rock and not hit someone coming to market with a new wearable device, they are not being effectively embraced in business processes and enterprise user interface design. They are also not yet forming networks of functionality.

B

Software defined anything

The open approaches of   OpenStack for Cloud OS and OpenFlow for software defined networking have definitely come into their own in 2014. There are still distractors who are fighting this rising tide but most see where this is headed and incorporating the shift into their mental model.

B

Software and analytics

2014 has definitely been the year for big data and analytics buzz words. I don’t think it has come to the point of there being widespread embracing of systems of action. Mobile is still viewed as something special and not just one of the many the interface points by most working in the ‘mobile’ space.

D

Software portfolio assessment

Of all the prediction areas, a fundamental reassessment of the software portfolio against the revised needs of the business, is an area where we’ve most missed our potential in 2014. Most organizations have not shifted to a holistic environmental perspective that will empower the organization and enable them to empower others. Organizations still need to assess what is abundant in this new world and maximize value from what will still be scarce for them and others.

A

Engaged and motivated employees will still be scarce

This is definitely true. In this age of automation, the value of good people and a predictable talent creation pipeline may actually be more important than ever. People are not fungible and as we increase our automation, that will be even more true, not less.

 

Based on these scores, my predictions for 2014 were at least not too conservative. My personal goal is to get close to a C+. If I get too high a grade, I am not trying to stretch my thinking (or yours for that matter) enough. Maybe I should strive to stretch enough to get at least one D??

 

My view is the same as when I finished up my post in 2011:

 

“Having said all that, it is a great time to be in IT. Most of our concerns are currently driven by an overabundance of capabilities that most organizations have not tapped into effectively. Those who can have the vision will be in for quite a ride this year as they look to do more with more.”

 

I should have my predictions for 2015 out later in December.

 

 

Automation prioritization

 

Since I have been putting out some posts on automation, I’ve been getting some feedback from coworkers. One was a post titled: 8 Questions to Ask before You Automate. It holds some useful perspectives to evalutate if automation is even applicable to a situation.

 

Back in the early 90s, I led a project called Knowledge-based Tool Design focused on improving the productivity of tooling designers for automotive manufacturing. We used the capabilities of CAD tools to try and automate as much as we could, related to the creation of the machines that facilitate car assembly. This was a high value effort, since late stage engineering changes in the car parts themselves have implications on the tooling and can delay the startup of manufacturing. Anything we could do to address the reengineering of tooling had a direct effect on time-to-market.

 

We would load the car component models that need to be clamped and welded into the CAD system and try to create automated techniques to define and design the tooling needed. After firing rays all over the place to determine entry routes for robotic arms holding the clamping and welding tools, it became clear that people can look at parts and tooling and determine routes for entry very easily compared to doing this programmatically. Creating these designs well definitely involved creativity and intuition.

 

What people could not do reliably was define the underlying Bill-of-Materials need to create that robotic assembly, physically. So yes, I learned back then that it is very useful to understand what people and/or computers are good at, when defining the right approach to address repeatable, higher-value, computationally capable tasks with automation first.

 

Whether it is designing tools, answering calls or writing software – even though the automation capabilities are radically improving, this assessment is still required. I usually think of it as a 3 dimensional matrix and the further away from the origin, the more likely the automation effort will be effective.

 

 automation axis.png

Just because we can do something, doesn’t mean we should do something, especially when there is a constraint on the effort available to tackle a set of tasks. We need to prioritize.

 

 

The need for automated environmental validation in IT

action 002.jpgI was recently reading the post When disaster strikes: How IT process automation helps you recover fast and it got me thinking about the need for automated environmental validation. Recovering fast may not be good enough if the recovery destination environment has changed.

 

In the software space, you can use jUnit or nUnit to codify the limits of the code and make sure it works, and breaks as defined. It can be a very useful component of a test first unit testing approach.

 

I was wondering if infrastructure automation efforts should include a similar capability that we can automatically test an environment to ensure its characteristics are up-to-snuff, before and after we make a change. These tests could either be run periodically, or as part of a promotion to production process.

 

Automating this validation would remove the human element from this tedious step. It seems like this would be a useful and possibly necessary step for cloud deployments, since those environments are dynamic and beyond the scope (and understanding) of the person who wrote the original programs. Maybe this is commonly done, but I've not talked to many who attack this issue proactively.

IoT standards war begins

tug of war.pngI seem to have done quite a number of blog posts in the last month related to the Internet of Things. I just noticed that there have been numerous announcements about standards efforts. This may have spurred me on. 

 

There are a number of them, but the three I’ve seen the most about are:

  • AllSeen Alliance that supports the open source project AllJoyn that provides “a universal software framework and core set of system services that enable interoperability among connected products and software applications across manufacturers to create dynamic proximal networks.”
  • The Open Interconnect Consortium with “the goal of defining the connectivity requirements and ensuring interoperability of the billions of devices that will make up the emerging Internet of Things. “
  • And Google (not to be left out) has defined Thread. Its goal is: “To create the very best way to connect and control products in the home. “ These devices all run over IEEE 802.15.4.

The IEEE has its own set of IoT standards efforts, but those haven’t been getting the press as the recently announced ones above.

 

It is clear that IoT needs standards, but if it is too fragmented there will be no standard at all.

 

Hopefully this will shake out soon, since standards will help make the services and the software needed that actually provide the value for the end consumer.

 

Other views about starting small but thinking big

Last week, I did a post titled: Start Small but think big, when transforming. Fairly quickly I got a note from Erik van Busschbach from HP SW that said he’d made some similar statements related to cloud adoption. In fact he even had a video about his perspective. 

 

 Think big, start small.jpg

 

Next week at HP Discover, I hope to track Erik down (who is the Chief Technologist, World Wide Strategy & Solutions for HP Software) and talk about the nuances of our perspectives. He also wrote a post on an HP SW blog about: Why the IT Value Chain is your blueprint for strategically regaining control of IT that also contains the start small but think big concept.

 

Even if we’re coming at the problem from different perspectives, the fact that much of what we’re talking about ends up at the same result is reaffirming. 

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About the Author(s)
  • Steve Simske is an HP Fellow and Director in the Printing and Content Delivery Lab in Hewlett-Packard Labs, and is the Director and Chief Technologist for the HP Labs Security Printing and Imaging program.
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