I travelled to Ireland last week, to attend the second meeting of the European Data Forum (EDF). The EDF provided travel support for my trip, and I am grateful to them for that. I was searching for evidence of ways in which smart use of data is having a transformative effect upon European businesses. Although some of those effects could be inferred from the presentations and hallway conversations, I was disappointed by the lack of focus upon explicitly enumerating these benefits. Plenty of people described what they did. Plenty of people showed pictures of their work, and their results. Very few told us how their efforts made anything better, cheaper, quicker, or more responsive, and that was a shame. This evidence really should exist. Was I at the wrong event? Was I talking to the wrong people? Or was I failing to see something that was actually right before my eyes?
So, with my disappointment out of the way, what was good? Actually, plenty.
Before getting there, though, some background.
The EDF describes itself as
a meeting place for industry, research, policymakers and community initiatives to discuss the challenges of Big Data and the emerging Data Economy and to develop suitable action plans for addressing these challenges. Of special focus for the EDF are Small and Medium-sized Enterprises (SMEs), since they are driving innovation and competition in many data-driven economic sectors.
EDF activities are coordinated by a group of projects funded by the European Commission (specifically projects under the auspices of the European Commission’s Unit G3, for which I have done work in the past.) Unit G3 is concerned with the ‘Data Value Chain.’ It is a Unit of Directorate G (‘Media & Data’) within the Communications, Networks, Content & Technology Directorate General (DG CONNECT) of the European Commission. Their org chart makes the structure somewhat clearer. Specific events such as last week’s meeting receive additional support from the European Commission, and from local organisations. With Ireland currently holding the rotating Presidency of the Council of the European Union, various Irish institutions were involved.
She was followed by Alan Shatter, Ireland’s Minister for the bizarre portfolio of Justice, Equality, and Defence. He talked (pdf) about the importance of investment in skills and jobs in Ireland, and the role of data in building a new economy;
The opportunities for Ireland and Europe in the area of Big Data and its analytics are, without exaggeration, unbounded. Large scale data analytics is quickly becoming the new frontier in productivity, in innovation, and in creating and sustaining a competitive advantage across both industry and the public sector.
As the local press reported, he also stressed the need for the upcoming revisions to Europe’s privacy and data protection laws to deliver something practical. But he went further than the familiar rhetoric about new frontiers, talking in concrete terms about money being invested in supporting the growth of these new businesses. His peers in Europe and overseas could doubtless match his aspirational words. Fewer of them could match his investment.
The strongest presentations, for me, tended to be those from industry. Windmills also featured highly, particularly in presentations from Ericsson’s Fiona Williams and Siemens’ Gerhard Kreß. Fiona talked about the EC-funded FINESCE project, and some of the work they’re doing to grapple with changes in the electricity grid. There’s a lot of talk about smart meters in the home, and the use of data to better regulate consumption and supply. But Fiona talked about a use case I hadn’t fully considered before. As we move away from centralised production and delivery of power toward a model in which centralised power stations are increasingly augmented by community-based windmills, domestic solar panels and the like, the grid needs to adapt in order to support the two-way flow of power… and the two-way flow of information about that power. The grid needs to switch from just dealing with spikes in demand to also coping with spikes in supply (lots of windmills on a windy night, or lots of solar panels on a sunny Sunday, when demand is low). If they aren’t managed properly, those spikes in supply can damage the distribution system. Managed – and anticipated – correctly, they enable companies running mainstream electricity generating power stations to reduce capacity, but that takes data, and time. Today, wind, wave and solar farms all too often stand idle as coal and nuclear stations that cannot easily be switched off provide power… despite the blowing of the wind, the rising of the tide, and the shining of the sun. Better data and better integration bring us closer to resolving that particular absurdity. Fiona also talked about ways to more intelligently manage the ways in which power is used. A pilot study within her project is looking at the feasibility of turning off low priority power consumption in parts of Ireland as the power output from the country’s wind farms temporarily falls. Electric car charging stations, for example, can perhaps be turned off as the wind drops, without anyone being inconvenienced. As the wind picks up again, they switch back on… and in most cases no one would even notice.
Gerhard Kreß’ talk of windmills took me in a different direction. European manufacturing giant Siemens is also (according to Kreß) Europe’s second-largest software house (behind SAP). Siemens builds windmills, generators, and other pieces of heavy machinery. But they’re increasingly in the services business, too. As more and more of their customers rent rather than buy, the business becomes one of servicing and supporting, and one in which maximising the return on a support contract is more lucrative than the margin on a sale. Anticipating failure becomes critically important. Siemens wants to service the turbine before it fails, but they don’t want to waste time and money proactively servicing something that could actually keep running for weeks or months without failing. Data and prediction clearly become important, and the profits to be found in squeezing a few more days out of a turbine are significant. Rolls Royce (renters, not sellers, of engines to the world’s airlines) are amongst those following a similar path toward future business models. Data and analytics are playing an interesting role, here, in accelerating this shift. From heavy industry to individual car ownership, the ability to track, model, and predict with increasing accuracy begins to turn existing models on their head. How much, Audi, for a contractual relationship to provide a new car that will drive 12,500 miles per year? The possibilities are fascinating…
Daimler CIO Michael Gorriz was also good. His key point, for me, was one he made in passing on the role of data in disintermediating dealers and others. The connected car creates interesting opportunities for a direct relationship between Daimler and the drivers of its cars… Audi, Ford and others, of course, are scrambling to exploit the same shift, and this links back to some of the implications from Kreß’ presentation.
DataMarket’s Hjalmar Gislason provided more interesting insights into his company’s evolving business model, and his slides are here.
And finally, for now, Telefonica’s Richard Benjamins delivered an insightful presentation that I sadly only caught the end of. He pointed to the growing importance of the Personal Information sector as a commercial opportunity, not just the data protection nightmare that so many seem to presume. It’s something I’ve been saying for a while, too… and an area I’ll be producing some more stuff in shortly.
Disclaimer: the European Data Forum supported the cost of my travel to this event.
(Cross-posted @ The Cloud of Data)