Live from SHARE 2017: Collaborative Mainframing

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I was delayed by 24 hours getting to this week’s SHARE conference in Providence, Rhode Island – more than 10,000 miles from my home in Australia. I was onboard my first flight from Sydney to Los Angeles when the captain announced that there was a problem with the “onboard mainframe” and they were going to have to reboot. Now I had no idea that aircraft run on onboard mainframes…or whether it was actually a mainframe…or how to reboot one. Does one use CTRL-ALT-DEL? Do you just turn it off and back on again? Some wise guy onboard suggested loudly that they “Call Bill Gates.” I don’t know how much this Mr. Gates knows about mainframes. Not much it would seem, because after about two hours the captain announced that the mainframe wasn’t collaborating (he may have said cooperating, but at that point I was a little preoccupied), and the flight was cancelled.

One problem with collaboration in the workplace is that it’s often devoid of all the facts – the supporting data. Decisions are made on the basis of hearsay and assumptions, rather than empirical evidence. But if you repeat a lie, or a false assumption, often enough does it become the truth? What value do we place on facts?

There is a lot of rich, valuable data stored on mainframes that could help support fact-based decision making and avoid false assumptions. But how easy is it to get to? Because when you think about it, a mainframe without timely, easy, responsive, flexible access – a mainframe where an IT department has to extract the data and load it into some kind of data warehouse in support of the business decision-making process – is really just a glorified, multi-million dollar file server.

So, what is “collaborative mainframing?” Is it a real thing? The answer is yes!

Imagine a scenario where, as an executive, I have multiple inputs to consider as I plan my business. Some operational data may come from the mainframe, some data from external or third-party sources and be in spreadsheet format, some data may come from our budgeting systems. Now imagine I have time pressure to make a particular business decision (who doesn’t, these days?), to pull together this information, interpret it, add some context and share with my team to reach a consensus decision. How am I going to do that?

As younger people are entering the management ranks, we are seeing a shift from “management by exception” to “management by analysis”, a new breed of business user who are data savvy yet information poor. As Inhi Cho Suh, GM, IBM Collaboration Solutions recently observed: We’re going from a typing and texting culture to a culture of conversations. A cognitive business empowers us to work as part of a seamless flow of information and conversations. It exploits our natural inclination for teamwork and creative collaboration. Data has little value without context, but by making mainframe data more accessible in support of a more holistic business view, we can leverage these information assets like never before.

As Charles Darwin is quoted as remarking, ”It is the long history of humankind (and animal kind, too) those who learned to collaborate and improvise most effectively have prevailed.” In the increasingly complex world of today, we need ever more timely, iterative, collaborative approaches to decision-making, regardless of where our supporting information resides. If we can do this effectively, then our business really can “take flight.” THAT is the essence of collaborative mainframing.

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Patrick Spedding

Managing Director, BI R&D at Rocket Software
Patrick Spedding is Senior Director of BI R&D for Rocket Software, and IBM Champion for IBM Collaboration Solutions. He is also a Non-Executive Director on the Board of Eastside Radio in Sydney, Australia. Prior roles include Director of Product Management for IBM Cognos, Director of Field Marketing for Cognos, Founder of Tableau partner See-Change Solutions, and SAS Solution Manager for BI and Strategy Management. Patrick's qualifications include an MBA degree in Marketing (AIU), Diploma in Management (University of Michigan), BSc (Hons) in Mathematics (Loughborough University, UK), Fellow of the Australian Institute of Management (FAIM), and member of the Australian Institute of Company Directors (AICD).

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One Response to Live from SHARE 2017: Collaborative Mainframing

  1. Gregg Willhoit
    Gregg Willhoit August 27, 2017 at 4:49 pm #

    I thoroughly enjoyed your discussion on mainframe Data and flexible and timely access and wholly agree with your conclusions. My comments are related to your onboard mainf the AP-101 and variants, and are only meant to inform as I am sure that that most folks are not cognizant of the fact that Space Shuttle Avionics were supported by the IBM 360 architecture . The IBM mainframe has had stellar record as the backbone of some serious onboard avionics systems and ground based flight and operational simulation and testing. One I am familiar with is the Space Shuttle’s Primary Avionics Software SYSTEM (PASS), which was adroitly complemented by 5 IBM 360 based onboard AP101s. Military planes in use today, still rely on IBM mainframe based AP101s or derivative technology for their avionics.

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