Reading in the newspaper this week about the technological advances in political campaigning set my mind wondering about whether there is an ethics/success trade-off in most areas of work, as well as in life generally.
I don't mean cheating in order to win; it's more about how you balance what you do, with what you think people want you to do. The article I was reading focused on the area of national politics. Technologies that we in the IT world are familiar with are increasingly being used to determine the "mood of the people" and to target susceptible voters. In the U.S. they already use Big Data techniques to profile the population and to analyze sectors for specific actions. The same is happening here in Britain.
What I can't help wondering is whether this spells the end to true political conviction. If, as a party, you firmly believe that policy A is an absolutely necessary requirement for the country, and will provide the best future for the people, what happens when your data analysis reveals that it's not likely to be as popular as policy B? Do you try to adapt policy A to match the results from the data and sound like policy B, abandon it altogether in favour of policy C that is even more popular, or carry on regardless and hope that people will finally realize policy A is the best way to go?
Some of the greatest politicians of the past worked from a basis of pure conviction, and many achieved changes for the better. Some pushed on regardless and failed. Does the ability to get accurate feedback on the perceived desires of the population, or of specific and increasingly narrowly defined sectors, reduce the conviction that has always been at the heart of real politicians? Perhaps now, instead of relying on the experts that govern us to make a real difference to our lives, we just get the policies we deserve because we all just want what's best for each of us today - and politicians can discover what that is.
There's an ongoing discussion that the same is true of many large companies and organizations. They call it "short-termism" because public companies have to focus on what will look good in the next quarter's results in order to keep shareholders happy, rather than being able to take the long view and maximize success through long term changes. Even though governments generally get a longer term, such as five years, the same applies because it's pretty much impossible to make real changes in politics in such a short space of time.
Of course, there are some organizations where you don't need to worry about public opinion. In private companies you can, in theory, do all the long term planning you need because you have no shareholders to please. You just need to be able to stay in business as you plan and change for the future. In extreme cases, such as here in the European Union, you don't even need to worry what the public thinks. The central masters of the project can just do whatever they feel is right for the Union, and nobody gets to influence the decisions. Maybe the EU, and other non-democratic regions of the world, are the only place where the politics of conviction still apply.
So how does all this relate to our world of technology? As I read the article it seemed as though it was a similar situation to that we have in creating guidance and documentation for our products and services. Traditionally, the process of creating documentation for a software product revolved about explaining the features of the product. In many cases, this simply meant explaining what each of the menu options does, and how you use that feature.
I've recently installed a 4-channel DVR to monitor four bird nest boxes, and the instructions for the DVR follow just this pattern. There are over 100 pages that patiently explain every option in the multiple menus for setting up and using it, yet nowhere does it answer some obvious questions such as "do I need to enable alarms to make motion detection work?", "why is the hard disk light flashing when it's not recording anything?", and "why are there four video inputs but only two audio inputs?" And that's just the first three of the unanswered questions.
Over the years, we've learned to write documentation that is more focused on the customer's point of view instead. We start with scenarios for using the product, and develop these into procedures for achieving the most common tasks. Along the way we use examples and background information to try to help users understand the product. But, in many cases, the scenarios themselves come from our best guesses at what the user needs to know, and how they will use the product. It's still very much built from our opinions and a conviction that we know what the customer needs to know, rather than being based on what they tell us they actually want to know.
However, more recently, even this has started to change. The current thinking is that we should answer the questions users are asking now, rather than telling them what we think they need to know. It's become a data gathering exercise, and we use the data to maximize the impact we have by targeting effort at the most popular requirements. In most IT sectors and organizations, fast and flexible responsiveness is replacing principles and conviction.
Is it a good thing? I have to say that I'm not entirely persuaded so far. Perhaps, with the rate of change in modern service-based software and marketplace-delivered apps, this is the only way to go forward. Yet I can't help wondering if it just introduces randomness, which can dilute the structured approach to guidance that helps users get the most from the product.
Maybe if I could get a manual for my new DVR that answers my questions, I would be more convinced...