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Motivation and software development
If people were not motivated to write software, computers would not have anything to do. What motivates a person to write software?
The source of human motivation may be intrinsic, as when pleasure is derived from performing the activity, or it may be extrinsic, such as being paid.
For some developers, writing software is a hedonistic activity. Intrinsic motivation continues to be the attractive force behind very many Open source projects.
People have to make a living, and being paid to write software creates an extrinsic motivation.
What do we know about human motivation?
The 1943 paper A Theory of Human Motivation introduced Maslow’s hierarchy of needs, which is now often used as a structure for thinking about motivation. The image below, from Wikipedia, shows Maslow’s hierarchy:
Managers have long known that various kinds of carrots & sticks can be used to incentivize people to behave in a particular way, i.e., applying extrinsic motivation.
Incentives are actively researched in business and marketing departments. Unfortunately, sometimes more fashionable topics, such as cognitive biases, divert researcher’s interest.
Despite its fundamental importance, developer motivation is rarely considered, let alone a subject of research, within computing departments.
As purveyors of intangible goods, the software industry is aware of many issues around motivation. Managers of software teams appreciate the impact of team motivation on performance. Team motivation is a perennial topic of discussion for the Agile coaches and Scrum masters I meet. Companies selling products offering an API hire developer evangelists, whose job is to motivate third-party developers to use this API.
Software systems that continue to be used become part of the fabric of larger, more complex, systems. The motivations of the inhabitants of complex systems can have many unintended consequences.
Motivation is an intangible that cannot be measured directly; its effect has to be inferred from the results produced by the behaviors it drives. Distinguishing between two diametrically different motivations can present a conundrum, e.g., distinguishing between developers following Parkinson’s law or striving to meet a deadline.
Books don’t usually have much to say about the human side of software product management. A well-known exception is Peopleware: Productive Projects and Teams.
My evidence-based software engineering book should have had a chapter devoted to motivation, but given its focus on publicly available data, I had to make do with several 1-page subsections.
Christmas books for 2020
A very late post on the interesting books I read this year (only one of which was actually published in 2020). As always the list is short because I did not read many books and/or there is lots of nonsense out there, but this year I have the new excuses of not being able to spend much time on trains and having my own book to finally complete.
I have already reviewed The Weirdest People in the World: How the West Became Psychologically Peculiar and Particularly Prosperous, and it is the must-read of 2020 (after my book, of course :-).
The True Believer by Eric Hoffer. This small, short book provides lots of interesting insights into the motivational factors involved in joining/following/leaving mass movements. Possible connections to software engineering might appear somewhat tenuous, but bits and pieces keep bouncing around my head. There are clearer connections to movements going mainstream this year.
The following two books came from asking what-if questions about the future of software engineering. The books I read suggesting utopian futures did not ring true.
“Money and Motivation: Analysis of Incentives in Industry” by William Whyte provides lots of first-hand experience of worker motivation on the shop floor, along with worker response to management incentives (from the pre-automation 1940s and 1950s). Developer productivity is a common theme in discussions I have around evidence-based software engineering, and this book illustrates the tangled mess that occurs when management and worker aims are not aligned. It is easy to imagine the factory-floor events described playing out in web design companies, with some web-page metric used by management as a proxy for developer productivity.
Labor and Monopoly Capital: The Degradation of Work in the Twentieth Century by Harry Braverman, to quote from Wikipedia, is an “… examination the nature of ‘skill’ and the finding that there was a decline in the use of skilled labor as a result of managerial strategies of workplace control.” It may also have discussed management assault of blue-collar labor under capitalism, but I skipped the obviously political stuff. Management do want to deskill software development, if only because it makes it easier to find staff, with the added benefit that the larger pool of less skilled staff increases management control, e.g., low skilled developers knowing they can be easily replaced.
Increase your citation count, send me your data!
I regularly email people asking for a copy of the data used in a paper they wrote. In around 32% of cases I don’t get any reply, around 12% promise to send the data when they are less busy (a few say they are just too busy) and every now and again people ask why I want the data.
After 6-12 months, I email again saying that I am still interested in their data; a few have replied with apologies and the data.
I need a new strategy to motivate people to spend some time tracking down their data and sending it to me; there are now over 200 data-sets possibly lost forever!
I think those motivated by the greater good will have already responded. It is time to appeal to baser instincts, e.g., self-interest. The currency of academic life is paper citations, which translate into status in the community, which translate into greater likelihood of grant proposals being accepted (i.e., money to do what they want to do).
Sending data gets researchers one citation in my book (I am ruthless about not citing a paper if I don’t get any data).
My current argument is that once their data is publicly available (and advertised in my book) lots of other researchers will use it and more citation to their work will follow; they also get an exclusive, I only use one data-set for each topic (actually data is hard to get hold of, so the exclusivity offer is spin).
To back up my advertising claims, I point out that influential people are writing about my book and it’s all over social media. If you want me to add you to the list of influential people, send me a link to what you have written (I have no shame).
If you write about my book, please talk about the data and that researchers who make their data public are the only ones who deserve to fund and may citations rain down on them.
That is the carrot approach, how can I apply some stick to motivate people?
I could point out that if they don’t send me their data their work is doomed to obscurity, because I will use somebody else’s (skipping over the minor detail of data being hard to find). Research has found that people are less willing to share their data if the strength of the evidence is weak; calling out somebody like that is do-or-die.
If you write about my book, please talk about the data and point out that researchers who don’t make their data public have something to hide and should not be funded.
Since the start of 2017, researchers in the UK receiving government research grants are required to archive their data and make it available. This is good for future researchers, but not a lot of use for me now.
What do readers think? Ideas and suggestions welcome.
Free range software developers: Are they cost effective?
I have just been reading an eye-opening article by Ramin Shokrizade about the techniques that online game designers use to extract money from players. Playing computer games and writing software have a great deal in common, two important characteristics they both share are being immersive and very enjoyable.
Reward Removal
From the article: “The technique involves giving the player some really huge reward, that makes them really happy, and then threatening to take it away if they do not spend.” Hmm, this sounds familiar. Beginner programmers are very resistant to deleting any code they have written, whereas more experienced developers are much less resistant to deleting code but they often put up a fight if an attempt is made to remove a feature they are responsible for creating.
“The longer you allow the player to have the reward before you take it away, the more powerful is the effect.” Wot! Remove this feature? What if somebody somewhere is using it?
“… uses the same technique at the end of each dungeon again in the form of an inventory cap. The player is given a number of “eggs” as rewards, the contents of which have to be held in inventory. If your small inventory space is exceeded, again those eggs are taken from you unless you spend to increase your inventory space.” Why are there no researchers with this kind of penetrating insight investigating how to make software engineering more cost effective? We continue to suffer from the programming is logic by other means world view, promulgated by the failed mathematicians that populate so many computing departments.
Premium Currencies
“To maximize the efficacy of a coercive monetization model, you must use a premium currency, …” [a premium currency is in-game money that is disconnected from real wold money]. The lesson here is that if you want software developers to make decisions relating to real world events you need to provide a direct and transparent connection to the real world. Hide the connection under layers of abstraction or vague metrics and developers can be easily fooled into making poor decisions.
Skill Games vs. Money Games
“A game of skill … ability to make sound decisions primarily determines … success. A money game … ability to spend money is the primary determinant of … success. Consumers far prefer skill games to money games, …. A key skill in deploying a coercive monetization model is to disguise your money game as a skill game.”
I think most developers consider their job to be one of making skillful decisions rather than one of making money for their employer, rationalizing that these skillful decisions result in their employer making money. Hmm, how much time do developers spend in skillful activity for what appear to outsiders as obscure coding issues; skillful activity is enjoyable while doing what makes most money for one’s employer can result in having to do lots of really dull and boring tasks. I cannot help but think that skill here is playing the role of a premium currency.
The big difference between playing a game and writing software is that in most cases a game has a well defined ending, a path exists to get there and players know when they get there. One of the reasons that managing software developers is like herding cats is that the ‘end’ is often very fuzzy and ill-defined. This does not mean that factory farming techniques are not applicable to software development, just that we have not yet figured out which techniques work.
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