Every once in a while I get into a conversation with someone who thinks about sensors and says something like “Yes, I can see some uses for sensors but not in my business”, so I have to give some examples...

Every so often I am asked something along the lines of “What will the Internet of Things mean to my job?” I’d like to describe a now, near, future scenario that takes place in almost every traditional  IT shop I am aware of. Something similar could be described in other industries as well.

Today when a system goes down, organizations will usually alert just about everyone who has half-a-chance of being able to fix the problem, in the hopes that it will address the problem. This interrupts many people, and attention fatigue can occur -- even though the organization knows a number of things:

From the enterprise context:

1)      The extent and type of the problem

2)      The organization that is effected

3)      If any kind of failover scenario was automatically executed

From the employee perspective:

1)      Who is trained on the issue (from the HR training database)

2)      What they are scheduled to do at this time (from their calendar)

Very little of this already “known” information is used in the response and notification process. Yet, it could be used to limit the number of people interrupted from 10 to 1 or 2, with an escalation process to extend notification if needed, improving the productivity of everyone involved.

In the future, sensing data from the phone could provide real time employee location information to limit the notification even further. Many people would sign up to give up this bit of information to the corporation if they would be interrupted less often. Preventative maintenance solutions could be used to predict when problems are likely to happen or notify personnel about system usage trends so that for systems that have some degree of redundancy they can have their maintenance performed with no impact on the end user. Almost all IT components today have some level of embedded sensing.

As changes are made to the Bill-of-Materials, training gap notification could be scheduled, so that the support organization doesn’t become a bottleneck for the deployment schedule.

Similar activities in retail (identifying trends and adjusting marketing and ordering) are easily identified. Healthcare prognosis recognition also uses many of these same techniques.

We’re talking about an ecosystem of information that proactively predicts the future needs and tries to align the organization to address that future state. This is an area that IT organizations and be creative and increase the flexibility of the organization, rather than just respond to events.

I was catching up on my email backlog, since I was on the road all this week and a story caught my eye: New Vending Machine Can Guess Your Age. This machine behaves differently based on the perceived age of the patron, in this case providing free samples to those it thinks deserve it.

I am not sure how successful this will be, but it is definitely an innovative approach to capturing attention of the consumer using sensing, mobile…

“Called iSample, Kraft’s vending machine dispenses free samples of trial products to their target audiences. A new pudding product, for instance, is targeted to adults. The machine determines the age of a customer, who then uses a smartphone with a custom code to get the sample.”

Back in May I mentioned some innovations that soft drink manufacturers are using to change the interaction with their customers.

Personal customization and sensing enabled custom interaction are all great examples of how consumer retail is enabling a more personalized experience but using standard, quality enforcing techniques that benefit both the consumer and the provider. We should see some great examples of these innovation expanding into other industries in 2012.

Big data has been a topic of conversation to the point where it is battling cloud as the buzzword of the year. The following article from ITBusinessEdge titled: Just the Stats: Big Numbers About Big Data provides numerous thought provoking bits of information about the current state of Big Data use in Retail, Healthcare as well as business in general.

There is more possibilities here than just the traditional perspective of the data itself. With all the computing capabilities there is much more that can be done with the abundance of data and computing. Opportunities exist in nearly every industry, both for static data as well as understanding the implications of data on the move --  turning data into the context needed to make decisions.

The speed and motion characteristics of data generation and transportation can be just as meaningful as the data payload itself. One of the places this is most evident today is in the social networking space, but within businesses similar metadata implication possibilities exist. Who is interested? Who is not? And what are they planning to do with the data, provides insight into the appetite of the organization – just like the derivative in mathematics is more meaningful for certain situations, predicting where objects will be.

Another very powerful aspect of the data is the relationship of the data to other data. What is collected at the same time and what can be derived from the relationship between the data? The shape of the data payload provides quite a bit of untapped context too.

We can analyze these new data and relationships in ways that were just not possible before.

The final interesting tangent I thought I’d mention is to merge the corporate data with data from other sources, like data.gov (which just turned 2 years old) and other large public data sets for analysis, in addition to internal systems that may have never had their data cross-pollinated. We have the computing and bandwidth capabilities, it is just our imaginations that are limited.

I saw this video of a project to shift the edge of the enterprise for grocery shopping to something more convenient for the consumer.

This is a good example of changing the definition of the enterprise interface. In this case they made “the grocery store” a thin sheet of paper (with QR codes) in a subway, a smartphone and home grocery delivery. That last part reminded me a bit of some of the failed dot com era efforts. This approach may have addressed some of the issues that made that effort fail. After all, home grocery delivery still exists in the US through PeaPod, Schwan’s and many local efforts.

The physical presence of the sheet of paper is why I called this a hybrid approach. They didn’t limit themselves to a web based or a brick and mortar approach. This approach is somewhere in-between.

Just because the grocery business has worked a certain way for the last 50 years, there can be changes in consumer expectation that makes these new ways useful to a specific consumer space. This is the issue described in the Innovator’s Dilemma where a new approach enters at a targeted market segment and then expands to take over market leaders.