Gregory Maciag

Europe Promotes IoT

The European Union is backing an open source organization called the Eclipse Foundation to develop an ecosystem for IoT, known as AGILE. This will bring together efforts across European nations, industry sectors, universities, and business organizations. Standards are at the heart of the work.

Deciding on technical standards has frequently been the trigger point for the growth of new technologies. Railway gauges, operating voltages, shipping container dimensions – these are just some of the standards decisions which led directly to world-changing developments.

People often confuse innovation with invention. But innovation doesn't have to mean inventing something new. What's important is you introduce something which is new to a particular situation – and make it stick. Time and time again, standards setting is the act which transforms good ideas into real-world success.

The European Union's support for IoT standards signals the trading block's intention to lead in the development of a hyper-connected world. Global competitors must take note.     eclipse

Farm the Data

One of the emerging sectors to watch closely is precision agriculture. With the world's population continuing to grow and the environment coming under greater stress, smarter farming is crucial for food security, health, and perhaps even peace.

I'm an outsider, but precision agriculture seems to be showing the typical signs of a movement torn between technology and business leadership. On the one hand, advances in precision ag will be driven by the invention and implementation of new sensors, networks, and apps – so it makes sense for technologists to be taking the lead. But on the other hand, the success of the technology is firmly allied to innovation in supply chains – to change throughout the business ecosystem – which suggests a need for a more commercial or managerial leadership style.

Of course, both drivers are necessary, so some kind of joint leadership is required. It won't be an easy relationship, because the dynamic will change over time. The way to steer a steady course is to focus with laser-like intensity on the data. The reason for the tech is the data; and the promise of the core business idea is also the data.   Funder

Data Standards - The Message Landed

Hudson Hollister, executive director of the Data Coalition, is one of our clearest and most compelling thinkers (and doers) on data standards. He gives great quotes – and it's always worth paying attention to him.

Hollister recently pointed out how appreciation of the value of data standards is accelerating in government: “It took us five years to do the Data Act […] It's been one year so far for the Financial Transparency Act.”

The Financial Transparency Act would mandate regulatory agencies to standardize the data they collect from the private sector. The great reasonableness of this measure is something to savor. We don't need to explain why data standards are important any more, because people have got the message about standardized data. The argument has flipped head over tail. Today, only a crazy person would argue for non-standardized data. And what would their business case be? I truly can't think of one.

Here's one more quote from Zach Noble's article on the progress of the Act. It's from Srinivas Bangarbale, chief data officer at the Commodity Futures Trading Commission: “Financial data standards should be mandatory, because without them, data would be garbage.”   FCW

Jump to the Future: Data Standards

Much has been written about the benefits to various communities of being able to jump a generation of technology. For example, some African countries were able to go straight to mobile tele-coms without installing national fixed line infrastructure. This saved money and time, but also created infrastructure for innovations such as micro-payments. In eastern Europe, Estonia emerged from the old Soviet Union with backward infrastructure but rapidly become the poster child for the digital economy.

Now countries have a similar opportunity with open data standards. Nations with complex and fragmented bureaucracies can jump straight to good data governance by using the tools and methods developed by organizations that have been through several additional cycles of systems evolution. They can engage their citizens directly through technology, embedding first-time data capture along with consistent data definition.

A secondary product is an improved environment for business and investment. A logical, open, and coherent data environment is becoming a vital factor in national, regional, and city competitiveness.   Open Data

Quote of the Day

“The cure for cancer won’t ever be found by doing research in silos. We need to shout from the rooftops that there are clinical research data standards that break down barriers, that by using these accepted, universal data standards, data can speak in a way we all understand, allowing us to learn from it and giving ourselves the chance to collaborate with that data – all in the effort to act, saving billions of dollars and, more importantly, millions of lives.”

– Nicole Harmon, Chief Operating Officer, Clinical Data Interchange Standards Consortium.   My Statesman

Costs of Dirty Data

I'm always on the look-out for examples of the costs associated with bad data management. The need for data management is pretty widely accepted these days, but it always helps to be able to put some figures to the risks associated with dirty data. Here's a good one:

“In 2014, the USPS published a report on their internal audit of Undeliverable as Addressed (UAA) mail. Of the 158 billion pieces of mail processed in FY13 almost 4.3% was classified as UAA, which totaled 6.8 billion. The total cost of processing these 6.8 billion pieces of mail was $1.5 billion comprised of costs associated with forwarding mail, returning mail, general waste and administrative costs. In other words, $1.5 billion of your tax money is wasted because of five attributes with incorrect data: name, address, city, state, and zip code. Extrapolate this example across the tens of thousands of medium and large-sized businesses in the US and the actual cost of poor data quality for US-based organizations is in the billions and with some have speculating it could be as high as several trillions of dollars per year.”

That's some punchline – several trillions of dollars per year. Notice also how the five data items mentioned here have their analogs in the core of every business: Items like customer names, account numbers, and any number of key production metrics are all likely candidates for dirty – and mismatched – data.   Snail mail isn't sexy, but the mail makes a fine, neutral model for any data-driven business. The tide of big data – most of it unstandardized – is a disparate flow, like traditional mail. At least mail users are supposed to know about zip codes – many of the new data sources which organizations are using today have no allegiance to any recognized standards.

Companies save time and money when their data is clean. They can only have clean data across the enterprise when they have data standards. Imagine how much it would cost to process snail mail if the zip code hadn't been invented and implemented. This is what some would-be data-driven organizations are facing. They need standards – fast.   AIM Consulting