Computing & software as ‘force-multipliers’: achieving objectives as an ‘army of one’ before requiring high performance teams

“When your vision of what you want to do is what you can do single-handedly, then you should pursue it. The day your vision (what you think needs to be done) is bigger than what you can do single-handedly, then you have to move toward management. The bigger the vision is, the further into management you have to go.” – Richard Hamming, You and Your Research, Talk at Bellcore, 7 Mar 1986, (PDF).

Your computer, kitted out with best in class software tools (mostly open source), can be perhaps the single greatest force multiplier that you have as a scientist, engineer, or mathematician. With the willingness to work hard and persist, and some skill at ‘software joinery’, you can accomplish more than you realize solely through your own capabilities. This article is about achieving those visions which you can do single-handedly, and how this enables having and testing the kind of bigger visions for which you need that next level of force multiplication that comes through larger budgets, high-performance teams, and management.

1. The problem: tackling and delivering ambitious ideas yourself on a low budget

For individual-sized visions, the kind that most students and early entrepreneurs have, the software tools you use and how well you use them can be central to your ability to prototype, test, and deliver ambitious projects, without requiring expensive IS/IT support. Even if you are in a corporate environment where IS/IT resource is available, its usefulness is often blunted by inadequate support, prohibitive overhead to involve, too slow iteration/cycle time, and problems with quality inherent in the outsourcing of any creative specification.

With software tools that you control yourself, you can become your own R&D army of one. Besides the feeling of liberation this brings, you’ll likely find that your increased abilities also increase your creativity when considering problems and their solutions.

Consider an analogy: if all you’ve got is a rusty machete, you probably won’t consider a solution that requires felling a tree. You certainly won’t be imagining possibilities that involve clearing a grove of trees. But put a chainsaw in your software toolkit, and felling one tree is no longer difficult and you might consider a solution that you would have otherwise overlooked. Add an army of programmable chainsaws that can be safely configured to work to precise instructions — now clearing a grove of trees is not much more difficult than felling a single tree.

The ability to experiment, simulate, and build fast prototypes, makes it easier to conceive of solutions that one might not imagine otherwise. By mastering your computing environment and extending your abilities, you’ll find that the ideas you conceive of will become correspondingly more ambitious as your own ability increases to do the tasks yourself.

In the metaphor, the ‘army of programmable chain saws’ may be simply a set of scripts or small programmes that you have written to automatically trigger on some input, take some decision, and run a process or special subroutine to generate some output. Put in a bit of fault detection and logging, and you’ve got a poor man’s data processing pipeline. This needn’t require complex programming. The key is that you are able to bring reasonable computing abilities to bear on problems in ways that bring solutions that would have seemed inconceivable before, closer to hand.

How to achieve bigger visions single-handedly, without relying on management? Cultivate the ability to generalize a single solution, link various discrete operations together, and automate a process so that it can be repeated many times, in changing conditions, always safely. When you get the various elements of your toolset working together as processing pipelines, you can get your computer to do almost anything you can imagine.

2. Investing to master your computing tools is investing in yourself.

“Knowledge and productivity are like compound interest. The more you know, the more you learn; the more you learn, the more you can do; the more you can do, the more the opportunity — it is very much like compound interest.” – Richard Hamming (Applied Mathematician), You and Your Research

Hopefully, this is enough to convince you to invest in better tools. Summarizing: your first reward is the signficant boost to your own productivity and the increased power you can bring to bear to tasks at hand. The second benefit, while perhaps less immediately apparent, is perhaps more important: increased self-reliance and the ability to be able to proceed without requiring that someone else has created an off-the-shelf package for you to consume. You are able to do more with less and to keep things simple.

Simplicity is in itself a key driver of long-term design success. The third, and perhaps greatest, reward is the ability, in principle, to conceptualize better solutions to more difficult challenges. This is a useful standard against which to decide whether individual tools are worth investing in learning, and how much effort to invest.

3. Building your computing capabilities

Assuming you have a clear problem. The first step is selecting an effective approach to exploring the problem: do you use existing off-the-shelf solutions (if available)? Or do you write a customized script chaining a sequence of filters (modules)? Or do you program the required functionality yourself?

Working in last two ways are not as hard as you might imagine. It can require building a script or small program that triggers on some input, takes a decision, and calls a process or subroutine to generate some output. Add a bit of fault detection and logging and you’ve got a poor man’s data processing pipeline. The result can be a working solution that would have been inconceivable before.

To continue reading this article and the toolkits, see Computing Toolkits