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Making M2M Data Actionable
Home Computers & Technology Technology
By: Roger Wilson Email Article
Word Count: 1091 Digg it | it | Google it | StumbleUpon it


The goal of an M2M solution is automating the flow of relevant data to the people and systems that have a need to know, and doing it in a timely fashion. A mountain of data is of no use by itself. It takes software applications to unlock actionable information hidden within that data mountain.

Managing the "tidal wave" of data received

Most M2M solution providers typically have available a Web-enabled interface for the viewing and basic interpretation of the M2M data being gathered. For a pilot project, or a planned small deployment, this can be a very attractive option, as it is immediately available and operational at a low cost. Data from an M2M solution can be housed internally using the company’s existing IT infrastructure, or the data can be hosted by a third party in a network operations center. It is not uncommon for an M2M solution to begin as a hosted model, then migrate over to the company’s existing IT infrastructure once the solution is operational.

Raw data to Good data to Verified data

When the amount of raw data being received from an M2M solution is small (a few devices transmitting infrequently) it is easy for one set of human eyes to validate data from the field. However, once a large scale roll-out starts to provide a constant stream of raw data, human eyes can no longer effectively perform this function. Enterprise software, developed either in-house or thru specialized third parties, is required to "scrub" the raw data to eliminate impossible readings and filter/flag suspicious readings. For mission-critical applications, this good data may need to be "scrubbed" a second time to compare against data obtained from a different source. A good example of this would be bulk inventory management. A comparison of the actual delivered product (electronic delivery ticket from the supplier) is compared by the enterprise software to the delivery change reported from the M2M data. If the compared difference is outside a preset value, an exception report is generated for investigation and resolution. This additional level of independent data verification can be very valuable to many departments within an organization. Operations receives independent verification that the delivery has been made; procurement receives verification to the amount received, and if there are discrepancies, maintenance has relevant data to help determine whether the problem is catastrophic device failure, network communication issues, or the result of a slow calibration drift over time. The company also receives a level of assurance that they supplier is not short delivering.

Making M2M data actionable to the enterprise

M2M demands that people think big. Early adapters implemented M2M solutions to eliminate painful & expensive human data collection processes. While this still drives the initial ROI of many M2M initiatives today, progressive organizations are looking at M2M as a way to create more "eyes and ears" in the field to gather data and delve deeper into information and processes. If more good data is made available to more departments within an organization, can it be used to make better decisions? Can the data be used to make the company run better? Below are examples of large deployments of M2M solutions providing actionable data:
* Electric utilities are implementing Advanced Metering Infrastructure (AMI), which involves adding M2M technology to electric meters at all industrial, commercial and residential customers. With a large deployment of "smart meters", the utility can reduce the "painful expense" of determining which customers have lost power during an outage. Knowing exactly which customer have lost power aids repair crews in improving the response to outages. However, usage data obtained from the smart meters will also allow the utilities to offer rate reductions for customers who voluntarily reduce their electrical usage during peak electrical demands, as well as a host of other services beneficial to the utility and its customers.
* A national supplier of bulk product with M2M technology installed onto the product storage bins, tracks inventory levels at their many customers. This solved the "painful expense" of sales people manually checking inventory. However, looking at this data from a national perspective, the supplier can easily identify specific areas of the country that are consuming more or less product. For product that does not have a stable consumption rate, this demand side information can be very valuable to corporate logistics and regional manufacturing.
* An outdoor advertising company with an M2M solution interfaced to their billboard lighting saves the "painful expense" of technicians driving around at night verifying the billboards are being lit properly. However, the M2M solution can also track and monitor power outages/restoration, bulb outages, power consumption, and provide a documented daily proof of performance.
* A heavy equipment rental company with an M2M solution interfaced to their assets reduces the "painful expense" of identifying the location of rented equipment, which can be very valuable during natural disasters or other times of high demand. However, by integrating engine sensors into the solution, the company is able to document equipment runtime, which allows the company to bill for actual usage, and flag and respond to equipment maintenance issues before it becomes catastrophic to the customer.
* An automated vending company with M2M technology installed into their vending machines saves the "painful expense" of manually checking inventory levels. However, by collecting data from their entire installed base across a large geographic area, the company is able to identify and easily track consumption trends for each product, helping to make each vending location more profitable.

Beyond preventative to predictive

Using M2M solutions built into machines during manufacture, equipment suppliers can diagnose many common problems remotely and perform predictive maintenance in advance of machine failure. Predictive maintenance reduces equipment downtime, as problems are identified and resolved before the machine shuts down, and also greatly reduces the time and expense of skilled technicians checking on equipment that is working. For mission-critical applications, this data is priceless, and for non-critical equipment, the ever falling costs of M2M solutions is making predictive maintenance a customer satisfaction selling point with a more profitable maintenance revenue stream possible.
The new element that M2M solutions bring to organizations is that now companies have new data to work with, data that is central to the way they operate and the value they provide their customers.

For more M2M information visit my blog at M2M Industrial Solutions

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