Sunday, June 30, 2013

Requirements Measures

I'm taking a short pause on the Changing Change series, as a large number of other questions have come up recently, and they deserve more immediate attention. Most of these are related to measures and metrics of various sorts.

Over on the IIBA LinkedIn group, Tammy Goslant asked if anyone could share an industry standard template for non-functional requirements (NFR). I have never seen one, and suspect this is because there is not best way to represent needs: it's always situational. Every organization finds itself modifying someone else's template to address the organization's industry, change methodology, maturity, and BA competencies (across all BAs).

Still, all templates for NFRs should do a few things really well. The most important, to my mind, is to ensure that measures for non-functional requirements make it easy to account for the ranges of acceptable operation for the solution.

Requirements Measures

In general, there are a spectrum of requirements measures related to the type of value that the requirements are supposed to deliver:

  • Functional Requirements tend to describe some potential gain to be sought.
  • Non-Functional Requirements tend to describe some potential loss of value to avoid.

Note the use of 'tend to' in this discussion. This is a spectrum, not a set of absolutes, and all requirements represent some mixture of potential gain and avoidance of potential loss.

Any kind of requirement measure can be placed in some range on the spectrum above.

  • Measures for potential gains tends to be relatively absolute. At the most basic level of individual features, the measure is 'works / doesn't work'. The functional requirements for a login process at the ATM are measured this way.
  • Measures for avoidable losses tends to be a range of acceptable - and unacceptable - behaviours. The ATM might log me in, but the response time should be 
    • within 5 seconds 90% of the time,
    • within 10 seconds 99% of the time,
    • within 15 seconds 99.999% of the time,
    • within 20 seconds 100% of the time.

Many requirements should be measured based on both kinds of measures - the potential gain, and the avoidable loss. The broader the scope of the requirement, the more common it is for both kinds of measures to be relevant. For example, business objectives generally involve a range of potential benefits and a range of avoidable losses (or ideal operating conditions).

Risk-Benefit vs Loss-Gain

Another way to consider this spectrum is to think in terms of solution benefits and solution risks:

  • functional requirements tend to focus on potential solution benefits.
  • non-functional requirements tend to focus on solution risks.*

Unlike change risks, which are managed as part of the process of making the change, solution risks should be managed as part of the solution. This may take the form of feedback or control loops, error trapping, performance reporting, or other mechanisms - but something needs to be built to address the risk. If you're an IIBA member, you can see a detailed, peer reviewed discussion of this in article CARRDS: Constraints, Assumptions, Risks, Requirements, and Dependencies in the Best Practices for Better Business Analysis (BP4BBA) publication; a shorter version appeared for the public in the December 2012 BA Connection Newsletter, under the same title.

Using these terms can be useful, especially when discussing the importance of non-functional requirements with stakeholders who are sceptical of their importance.

Acceptable Ranges

In the ATM example, the lower limit of the acceptable range was zero seconds. In many solutions there is both a minimum and a maximum to the acceptable range. Jacob Nielsen mentions one such case in his article, Response Times: The 3 Important Limits. Nielsen says,

"Normally, response times should be as fast as possible, but it is also possible for the computer to react so fast that the user cannot keep up with the feedback. For example, a scrolling list may move so fast that the user cannot stop it in time for the desired element to remain within the available window."
Servers should operate in a temperature range. Supply chains should be optimized so outputs of one process happen at a rate very similar to the inputs for the next process. Sales demand that drastically exceeds the capacity of the manufacturing facility can lead to angry customers and lost profits.


There may be no industry standard template for the recording of non-functional requirements - but there are some things that all templates should have. Coherent, clear, useful measures are at the top of my list.

* From a Business Analysis Core Concept Model (BACCM) point of view, the term 'risk' and 'potential loss event' are essentially the same, so the 'solution risks' can be rephrased 'events with the potential to case a loss of solution value'. 

Thursday, June 20, 2013

Automation And You

Last week I mentioned that there are some trends in human behaviour that go back to before recorded history - perhaps before we were human. This week we're going to look at the one that I find most personally fascinating: automation.

Cyborgs are humans with tools integrated into their physical forms and behaviours. Glasses. Pacemakers. Pencils. Cars. We're all cyborgs.

Automatons are machines with humanity integrated into their physical forms and behaviours. Lighters. Printers. Plumbing. Phones. Automation is everywhere.

Notice a similarity?

For hundreds of thousands of years humans (and our progenitors) have been automating ourselves into tools, and integrating our tools into ourselves. Other animals create and use tools or integrate them into themselves; we do both on a scale unparalleled in the rest of nature. We do this to preserve life and quality of life: artificial hips are one thing, and implanted artificial lenses that allow you to see the ultraviolet are another (thank you SGU!). Our dependency on technologies and tools dates back far further than most people consider. Only one primate survives with a digestive system that is tiny and weak.* Only one animal can throw at all.**

Humans are not just tool using apes. We are apes made of tools, physical and mental. On the physical side, our brains are built to integrate the tools we use into the our sense of self. When a driver says "I can feel the road" or an athlete can "feel the puck" it's not a metaphor or imagination. (For a really deep dive into this check out "Natural Born Cyborgs" by Andy Clark, published by Oxford University Press in 2003. The Brain Science Podcast is also a great resource.)


Automation and cyborization are important because they are both part of our nature. It bears repeating: we are not just tool-using animals; we are animals that integrate tools into ourselves and ourselves into our tools.

Fire and ballistic weapons are baked into our DNA, and show up in our guts and our shoulders. In the first case, the capacity to cook food liberated so many calories that our physiology was transformed. In the second case, the capacity to accurately throw random objects with force likely did something similar.

At the most fundamental level humans are animals with two extreme traits. We'll talk about social another time; auto-cybo-mati-rg-on has more territory to cover.


What does this have to do with being a Business Analyst?

Many of the things that BAs do today are hard to automate - but at some point in the past everything was hard to automate. The integration of humans and tools isn't over. It can't be. Firestarter was a job. Printer was a profession. Computer was a profession. Those were hard, yet they were turned into matches and boxes that sit on your desk. Human are not humans without tools.

I describe this in three Automation Axioms of human behaviour:

  • AA1: Humans automate every behaviour we can using tools. 
  • AA2: Humans amplify every capacity we have, through tools. 
  • AA3: Humans invent new capabilities to have, with tools. 
To be clear - when I use 'axiom' it is because I have not been able to discover behaviours, capacities, or capabilities that we have not tried to automate, or do not want to automate. If you can take any or all of these as a hypothesis and test it - do! Point out research that falsifies any or all of these assumptions.

So why does this matter to BAs? It matters because the automation of entire industries, and the job displacements that resulted - they're not over. Knowledge workers are next.

I was able to dictate this sentence into my computer, with no effort whatsoever. Transcriptions were once a purely human job. What will happen when a cell phone on the desk can record everything that you do in an elicitation session? What happens when that phone can translate all the diagrams on the whiteboard, all the words that were spoken, everything that was written down - and turn it all into a document that is indexed and useful? What happens when the cell phone can ask the questions, project the diagrams, and record the responses, without human intervention?

It is going to happen. Business Analysis is hard work that requires expertise, subtlety, and knowledge, but betting that our profession won't be automated is betting against human nature - and that's a sucker's bet.


This does not deny the pleasure we feel performing tasks "from scratch." My wife and I have recently started making (excellent if I must say so) bread at home. I am the bread machine (the one kneading the dough), and my shoulders are getting nicely toned (we do like the heavier loafs). Still... "from scratch"?

We don't grow the flour.
We don't milk the cows.
We don't press the mixing bow.
We don't build the tabletop.
We don't mine the natural gas for the oven.
We don't build the oven.
We don't mine or smelt the metal ore for the oven.
We don't assemble the tools to mine or smelt the ore for the oven.
We don't blow the glass for the flour canister.

We don't ... get the idea.

If humanity (not individual humans) are engaged in a long term integration with our technologies, it is easy to fear the dystopian future where we are subjugated or subservient to our own creations. This concerns me, in the same way that house fires and car accidents concern me. I take reasonable precautions, and then get on with baking and driving.

In part, I'm not afraid of the future because there are things that can not be automated, in the same sense that there are things that can not be bought. WE have a special name for the act of buying love, and for a reason. Humans are not rational animals, and the intent behind certain interactions has meaning.

When your mother kissed your cheek good-night - that isn't something that can be automated. Sure, a machine could plant a kiss, but if the automaton can share the emotional interaction involved in a good-night tuck-in, it can't really be classified as a machine. In the episode "Measure of a Man" from Star Trek: The Next Generation, the claim that "Data is a toaster!" was clearly not true. But why? R2D2, HAL - these were not really machines in that sense. They were sentient beings clad in strange shapes and colours. They were people.

Conclusion: Automation and You

This long term trend of human-tool interaction should be of special interest to BAs. Automation will continue to enable our role in fantastically powerful ways - which is the same as saying that it erodes the things that make our role difficult. Creating androids that we relate to as people is a very challenging technical problem, and one that won't be solved quickly.

Your star power as a BA is rarely based on your virtuosity with a tool or a technique. Sure, Word Wizardry can help - but WhiteBoard Wizardry can change lives too. Consider the parts of your role that machines won't be able to do any time soon. Most of them have to do with human contact.

Start a video chat.
Pick up the phone.
Shake hands.
Build relationships.

Automatons can do a lot, but they can't be human - yet.


* The one that mastered fire.***
** The one that mastered spears.***
*** I am aware that other primates, such as Neanderthals, had some throwing ability. Not like us, though.

Sunday, June 9, 2013

What is Innovation?

In last week's article, we covered four major advances in how people perform changes. The first three have been around in various forms for thousands of years: the Making itself, Tested for quality and variance, Controlled to coordinate people and resources. Modern project management is only about a century old, and can in many ways be traced to the building of the Panama Canal. The latest advance in our approach to making changes is Business Analysis. This discipline has appeared in a myriad of forms, ranging from enterprise architectural disciplines, to design thinking, to the community-driven standards that International Institute of Business Analysis® (IIBA) manages and sustains.

Being part of the latest - and perhaps even the greatest - transformation of change brings me great pleasure. As a Business Analyst, it is also clear to me that "latest" is not the same as "last." Entirely new categories of industry are appearing at an accelerating rate; the complexity of change is increasing; technological advances are not slowing down. "Greatest" is a value judgement that depends on the context, and our context is arguably more dynamic than any time in history, excepting world-wide* catastrophes, such as war, famine, and pestilence.**

Image Source: I-BADD Keynote by Julian Sammy, Head of R&I, IIBA
Business Analysis works as long as the needs are understandable. There are things which we can not know and can not anticipate. What do we do about disruptive, unpredictable change?


In it's most basic form, innovation can be represented as a simple equation:

Innovation ≥ Invention + Delivery

It is not enough to create something new, nor is it enough to deliver something. The combination of invention and delivery is greater than the sum of the parts.

Lightbulbs are the iconic innovation story: Edison innovated, where others invented. He took an invention that had been proven as possible almost 100 years before, and made a practical product. It wasn't just the bulb that was the big deal, either: the whole supply chain for electrical power distribution was rather important too.
In Edison's time, there was time to operationalize an invention. Now new categories of technology appear every few years, as do new business models. These both disrupt older models. In this environment, it isn't enough to see an opportunity in the market, and solve the problem first. Innovation includes the capacity to adapt to environments that don't exist at all, and that may be unimaginable.

Business Analysis breaks when you reach the edges of the imagination; it is after all, an analytical discipline, and uses analytical tools. It is also slow. This is an asset to the profession: taking considered action is almost always more effective than instant reaction.

So what do we do about conditions that are inconceivable? What of reactions have to happen faster than considered thought to have any meaning at all? Can any organization develop the capacity for immediate reactions to unimaginable conditions?

One approach to this situation is found throughout nature: plant a huge set of seeds, each with different characteristics. Some will excel in local conditions; some will not. The seeds that are pre-adapted to the conditions that exist when they germinate are the ones that survive.

This is an important idea: the seeds that grow are adapted to conditions that do not exist when the seeds are planted, because they lie in the future. When the seed starts to grow, the conditions may match the seed's ideal conditions, or the conditions may kill it.

One characteristic of modern innovation is the capacity to plant seeds that can grow (and be profitable) in conditions that are unimaginable today. In business, this means a persistant, deep-seated corporate culture that demands many small changes be attempted. These small proofs of concept will have a high failure rate, but should be examined carefully (something that BAs can do, and do well). Figure out what conditions would have made that seed a success, and bank it just in case those conditions come to pass.

Another characteristic of modern innovation is the capacity to nurture the seeds that are growing, while avoiding the sunk cost fallacy. This is a very hard problem, particularly because it requires a culture that values the past while relentlessly discarding it. Google and Apple are at the forefront of this behaviour today.

Next Steps

In the next few weeks we'll look at several key ideas that play into this modern concept of innovation. This will include delving into the way that operational disciplines have developed over time: practices like specialized people, assembly lines, and just-in-time supply chains have changed the world. We will also explore some trends that are rooted deeply in fundamentals of human nature and span thousands of years: increasing complexity of change practices is one; automation is another. A propeller-head post on the nature of change will also be coming - though that one involves set theory and weird mathematical notation, so I may post it as a separate series.


* Historically relevant and broad uses of 'world-wide'.
** Often provoked by climate change or ecological collapse.
*** I suspect there is another set of disruptive transformations occuring in these practices as well.

Sunday, June 2, 2013

Makers were first. Who will be last?

Humans make changes to how we make changes - but first and foremost, we make changes to the world around us. When Dan Pink talks about the science of motivation ( he's talking about this drive to effect the world.

So how do we make changes?


Image Source: SXSW - MIY: The Maker Movement.
A maker is an individual contributor who explores the world, fiddles about, and makes a change. A Maker may be an artisan, artist, scientist, engineer, inventor... the list is long. All makers have common threads: curiosity, expertise, and a preferred medium or form (which may change over time). Musicians make music. Teachers are makers too: they work with minds and bodies.

Makers can be contrasted with Doers, who use what's been made. Everyone is some combination of both; it is a spectrum, not opposites or an isolated, forced choice.

Without Doers, organisations can not be sustained.

Without Makers, there is no "controlled transformation of an organisation"... or of anything else.
This mode of change works as long as it's a change one maker can create alone. It breaks the moment that more than one person is making one change.


Image Source:
As soon as two people are working on one thing, the quality of the output will change. Maybe it goes up, maybe it goes down, but it will be different. And what if two makers are working on different components of one thing? Can the stonemason build the door for the house? Individual contribution breaks down as soon as the work requires more than one human; Testers ensure that the quality of that work high enough. Consistency, repeatability, quality - the Tester makes sure that Makers working together produce results that meet a certain standard. (Testers also work with Doers on sustaining an organisation - but that's a topic for another day.)

This mode of change works as long as the change is simple enough to coordinate spontaneously. It breaks as soon as logistics get complicated.


Image Source:
What happens first? After that? And then? What if it doesn't? Do we have the resources (people, processes, tools, information) to make it happen? Where is that input coming from? When? For how much money?

Testing the quality of a change is necessary, but it only matters if the change is completed. Controllers and coordinators - often called Project Managers in the modern day - deal with the logistics of a change. Controllers make it possible to coordinate tens of thousands of people for years, to resolve a single question or solve a single problem.

This mode of change works as long as the need is easy to understand and describe.


Image Source: Foundations of Software Engineering, Kenneth M. Anderson
What are we trying to achieve? Why are we working toward this outcome? Will it matter if the context changes? Who gets value from this? What kind of value? What about needs that can't be stated in 21 words?

Controlling a change is only valuable if it's a valuable change; it only matters if the purpose of the change is understood. When the purpose is simple, Control is enough - even when the solution is astoundingly complex. The Apollo program is a brilliant example.

"...the goal, before this decade is out, of landing a man on the Moon and returning him safely to the Earth."

A change that some had imagined but was at that time impossible, and the purpose articulated in 21 words. It was realised through project management, testing, and making. In the end, the Makers built something insanely complex and with shockingly high quality. Controllers made it happen in the right order - and made it happen at all.

This mode of change works as the change can be described in a few dozen words. Small words. Quoting from Galaxy Quest (one of my favourite movies of all time), "Explain as if to a child."

In case it isn't obvious - the change discipline that is founded in understanding is Business Analysis.

This mode of change works as long as the needs can be understood, at least in principle. Information theory, mathematics, and basic logic all tell us that there are things which we can not know, however. What do we do about needs that can not be directly anticipated? What do we do about disruptive, unpredictable change?


...and that's what well talk about next week.

Update 2013-06-08 - I just found out about the integration of comments with G+, so I'm updating this post and reshareing.