Collaborative Learning in Distributed Environments

I have been reading about other uses of cloud based and mobile technologies and I came across some examples of adaptive learning, which I thought were really interesting. Initially I heard about them from the beloved Radio 4. The two examples I wanted to discuss both come from education and rely on mass adoption by a large remote and distributed community. I suppose you could say they are business to consumer, although that label feels odd for education.


Stop the projects, I want to get off

People often ask me how our cloud service for production data management, production reporting and production allocation is different from traditional solutions. This is a hard question to answer, as I want to describe the distinct values of my product and company without seeming to denigrate the competition.

In addition, it’s really hard to provide quantitative information. We think an EnergySys solution is hands-down the fastest, most cost-effective and most configurable choice for customers, but this is largely based on anecdotal evidence. It’s rare for two companies to have delivered systems for the same assets under the same conditions, though we do have a fair amount of experience of replacing competitor systems, so an exact comparison is difficult.

However, during the course of a discussion with a company looking to replace a competitor system I realised that part of the answer lay in the conversation we were having. This user kept talking about projects. Projects to implement new assets. Projects to add new fields or wells. Projects to upgrade the basic software. Everything was a project. And projects required substantial time, money and resources, even just to get a basic upgrade of the software done. In fact, for this user an upgrade cost almost as much as the original project implementation! EnergySys isn’t like that. 


Please stop talking about private cloud

I made a presentation at yesterday’s conference on Developments with the Digital Oilfield in London. The title of my talk, “Why private cloud is a cul-de-sac of doom”, was somewhat tongue-in-cheek, and intended to be mildly provocative. However, I had a serious purpose, in that the words and terms we use to describe things are important in creating clarity and driving ideas. Misusing them dilutes their power and ultimately diminishes opportunities. In that context, the term “private cloud” is one that has minimal value and causes confusion.

In my talk, I referenced the NIST definition of cloud computing, and my version of the three key elements that embody the transformational impact of the cloud:

  • A usage-based payment model, whether that’s per user, per cycle, per cpu, or whatever
  • Rapid elasticity, or the ability to seamlessly grow and shrink your demand without needing to stop to add new hardware or software
  • No barrier to exit or entry

Why low cost is not enough

In a recent posting to LinkedIn, comments from an oil company contact were reported to the effect that high levels of investment in hydrocarbon allocation systems were unsustainable. The poster invited people to consider whether it was time to concentrate on value for money. I won’t link to the post, partly because it was on a closed group, but also because I wanted to focus on the general issue that it raises, rather than the specifics of the post.


The cloud: Why not, not why

When I do presentations of, and I show how good it is and how it can transform a company’s business, I’m often asked whether it can be installed locally, and why we’re delivering our solution in the cloud. The answer to the first question is “no”, but the second question requires a more considered response. Why, indeed, do we deliver our solution for production reporting and allocation in the cloud?