I was at a business lunch at SMU the other day and one of the people sitting next to me asked “Why now?” for this shift in computing. I told him that organizations have an ever increasing range of computing devices that are being used in more places, by more people, every day. They provide greater volumes of information and levels of detail to the organization.

Having this abundance of information is not sufficient for an organization to compete more effectively. The data needs to be used to quantify uncertainty and allow the organization to adapt to the needs of the marketplace more rapidly and effectively than its competitors. The technology needs to enable action. The automation of normal and the channeling of attention and creativity are key facets of generating value from Machine-to-Machine efforts.

There is a great deal of opportunity for the innovation of automated business processes through sensing in almost every industry. People want solutions that are:

• Simple and yet have deep understanding
• Secure and yet collaborative
• Mobile and yet powerful
• Low cost and high quality
• Standard and yet customizable

We are living in a world of contradictions and with contradiction comes opportunity and a need for innovation.

This widespread need is not limited to businesses, the consumer space has conflicts in expectation as well, and those bleed into the business environment. Recognizing the conflicts and enabling them to overcome them will generate customer preference.

HP has a long history of investment in every layer of machine-to-machine value generation for business. With the addition of EDS, there is also a track record of services to support some of the largest data gathering and machine interaction system delivered. HP labs has created sensors for gathering information about vibration and chemical compounds as well as particulate counting, defining some of the foundational sensors to understand the world around us. Currently, HP has efforts underway to deploy and collect information from millions of sensors to provide greater insight about underground petroleum resources. HP has collected sensor information for utility companies to improve the efficiency and delivery of water and electricity to municipalities. The efforts to push the envelope of data analytics has also had significant impact in the identification of opportunities for HP's clients.

A contest being done by the HP TS organization and had to pass it along...

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Machine-to-Machine is a buzzword in computing today concerning information moving between computing devices to perform functions. Although the machines play an important role, with one usually on the edge or outside of the enterprise, they don’t really create new value for the company. What this does do is provide more opportunity than ever to gather data from the edge of the enterprise, consolidate the data into information and drive decision making with greater clarity, transparency and less latency than ever before.

There are numerous layers to gathering value from a machine-to-machine effort: 

• Sensors and Controllers – these are the devices in the field that gather the information about the environment. They may even have enough sophistication to make adjustments to controls based on the collected information. Examples of devices in this layer are: RFI devices, thermostats, Programmable Logic Controllers (PLC). They may also be sophisticated equipment that provide information to the enterprise as part of their function.
• Data Transport – this layer transports the information to the enterprise and may be implemented as a mesh or dedicated network and be wired or wireless. Today wireless communications like ZigBee and 801.11x are common methods of moving the data from the device to the enterprise.
• Data Integration – once the data has entered the enterprise it needs to be modified to conform to the organizations data structures. Middleware techniques used to make it the right format and provide relatively simple alerts for anomalies found. The data may need to be compressed, aggregated or kept in its raw form.
• Analytics – this is the layer were significant pattern recognition techniques can be applied to identify anomalies and triggers to attract the attention of the organization can be generated. This is the core system that understands the context of the enterprise.
• Alerts/Displays/Reports – this is where the user is notified. It should understand the context of the individuals as well as their preferences. If done properly a minimal number of unnecessary interruptions are generated in the organization since messages are targeted at the minimum number of personnel to address the situation and expanded as needed to meet the severity and the timeframe for response. This layer also provides the historic perspective of the information gathered.
• Action – without action everything else is a waste of time

There is a great deal of opportunity for the innovation of automation of business processes through sensing in almost every industry. People want solutions that are:

• Simple and yet have deep understanding
• Secure and yet collaborative
• Mobile and yet powerful
• Low cost and high quality
• Standard and yet customized

We are living in a world of contradictions and with contradiction come opportunity and a need for innovation.

This widespread need is not limited to businesses, the consumer space has conflicts in expectation as well, and those bleed into the business environment. Recognizing the conflicts and enabling them to overcome them will generate customer preference.

We are talking about an “And not Or” world, where people want to choose among things, not between things. We're in a world where organizations want decisions made in real-time based upon what is likely to happen, not just reacting to the past. In order to get that level of sophistication, machine-to-machine techniques will become commonplace and the use of sensing to recognize the context of the situation and either handle it or alert the organization so its creativity can be brought to bear on the problem. This will change the role of systems and personnel, since it is not about sense and response but instead about sensing, anticipating and validating, shifting the role that information technology plays in generating value.

I was catching up on some of podcasts that I’d stored up when I came across a few that reinforced one of the issues I have been talking about for a while – attention engineering. NPR’s Science Friday had a couple of podcasts dealing with issues relating to human attention and missing important events that are taking place.

The first is titled Stealing Attention and the second one is How We Pay Attention. Both demonstrate how easy it is for us to miss important details of what is going on around us when we concentrate on specific areas. They have some great videos that demonstrate the phenomenon.

With our technological advancement, we have all this computational capability and data coming at us. Making the most of it means we need to think about how presenting the information in a context that we can consume or even handle it for us so we are not interrupted by “normal” information can be critical to maximizing value. I was in a discussion just this week with an organization that was talking about hosting their systems with cloud computing or bringing in a SaaS set of functionality. If the consistent user interface issues are not considered, the likelihood of significantly higher business value creation will be slim. In fact, if there are enough inconsistencies it could be distracting enough to prevent you from seeing the “gorilla in the data”.

My first thought?  Organizations must look at this impact of the IT systems on the way the users think, when they plan their investment in their applications.