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

Looking at the smart home and wondering about the smart enterprise

business questions.pngI came across this post about a self-actualization-house and it made me wonder about the application of these techniques within an enterprise. The concept of this house definitely takes the concept of an environmental view of the IoT to a whole new level.

 

Although the concept of a house that can create energy and address its needs would be nice for an enterprise as well, there are so many more resources that enterprises consume that needs to be optimized beyond just energy.

 

With the use of analytics and other techniques having a ‘dumb’ enterprise may be just as unacceptable as the ‘dumb’ house in the article. Business process autopilots will be as common as thermostats. I’ve not really thought about the needs from the same level of stage 1-8 that the article has done for the house but I can see it coming. Taking the articles final thoughts and replacing:

Born -> Hired

Home -> Business

Live -> Work

Family -> Co-workers

 

Leads to an interesting perspective of the enterprise of tomorrow.

Data Privacy Day - January 28th

security compromize.pngToday is Data Privacy Day (@DataPrivacyDay) – 7th annual. This occurs on January 28th and its purpose is to raise awareness of privacy concerns and promote data protection best practices.

 

Last year really drove home the issues related to data privacy, with more and bigger issues than ever before.

 

The Christmas Story movie had a scene that stated that the only room in the house a preadolescent boy can have any privacy is the bathroom. In our modern world, with devices and sensors everywhere (for some of us) even that bastion of privacy is fleeting.

 

Having a day emphasizing the need to look at the long-term impact of data collection, use and protection practice (possibly even performing a self-assessment) seems prudent.

Are cloud failures different and more common?

Cloud failure.pngWith every technology there is a lifecycle and it cloud computing must be coming off the top of the top of the hype cycle with the number of stories similar to: The worst cloud outages of 2014.

 

And follow on stories like: Cloud failures will happen. Are you ready? It is prudent for articles to make statements like:

“Even if you only use the most reputable cloud services and products, things are bound to go awry from time to time so it’s crucial to be prepared for failures.”

 

And the ever popular: Why some cloud projects fail? Granted there are some staggering failure rates for cloud projects, but there are significant failure rates for all technology related projects.

 

Many of these patterns of failure are not unique to cloud. It usually gets down to a few issues core to every IT project:

  1. Know the business expectations/requirements and how to measure them.
  2. Have clear executive support
  3. Start small and make adjustments based on facts – iterate. If you don’t get what you expect make changes.
  4. Keep the big picture in mind (in many dimensions). After all, you’re trying to address the needs of the enterprise and not usually just a silo, at the end of the day.

Moving to cloud implies moving from operational thinking to a services mindset. Too many companies still bother about the underlying technology, forgetting to realize they now buy and integrate a service.

Data and decision latency expectations shifting

Analytics time.pngOne of the issues I’ve talked about many times over the year is the need to shift our understanding and expectation of latency and action. I came across this post: Analytics Time Lags Result in Lost Opportunities. It also discusses the fact that the data gathering and analytics that were great a short while ago are now viewed as insufficient, stating that “72% of analytics and business leaders surveyed were dissatisfied with the time it takes to get data-driven results”.

 

Unfortunately, it didn’t really do more than imply that solutions exist. Fact is most solutions deployed today are based on hindsight. There is little doubt that the vast amounts of data available are going to require an exceptional command of information, far beyond just hindsight. It will require a refocusing of skills and perspective that are based on generating value from the abundance of computing and data available. This will require new techniques for computing as well as data gathering and integration. The work going on in HP labs related to The Machine will help address these needs, when this platform is released.

 

We have data coming in from sensors and mobile devices creating an ever increasing amount of Dark Data where value can be generated. We can also build context from the other data about what happened when, who or what was involved or happened at the same time. This derived data or metadata can sometimes be more valuable than the raw data itself, since people don’t really make decisions off the data but the context the data describes. Organizations are recognizing that all this data will provide a depth of understanding about what happened in the past, present and future that we’ve not really taken advantage of before.

 

We can develop a greater depth of understanding about what is happening right now that can enable us to automate decisions or concentrate that rare resource – employee attention - on those areas that really need it. There are relatively new technologies that most teams have not even looked at like software defined networks… that can operate on data on the fly instead of just data at rest. This will eventually enable a more active, organizational approach to tackling opportunities.

 

Finally, over the years we’ve learned that getting to zero response time is very difficult. It may actually be easier to move to a negative response time, where you predict what is likely to happen and adjust to be ready to address it or even shift the outcome. Tools to address all these various perspectives of data and enabling right-time decisions are available to improve your ability to optimize time-to-action are available today.

Wisdom of the crowds applied to a range of topics

crowd2.pngThe concept of having experts vote on what they think is the answer has been around for a while. It is essentially the foundation for The Wisdom of Crowds. I’ve posted before about the use of this technique to predict the adoption of technology.

 

A new site out of George Mason University called SciCast is taking a similar approach but tackling a number of industries beyond just the technology sector. You can see what others believe will happen in your favorite area.

Labels: Future| Prediction
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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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