Chaos theory suggests small changes in initial conditions can result in vast differences in the future.
It implies that massive, unpredictable events can be directed with a few small early changes in the right place. While this is a simplification, it’s a useful one when it comes to enterprise software development.
Consider how many times a tiny decision has snowballed into a major situation.
It rarely seems like a significant decision when it’s made, but by the time developers spot the issue it’s an avalanche that threatens the entire project.
It seems impossible to avoid those random setbacks. After all, no developer can see the future.
In practice, though, developers can head off the majority of unpleasant surprises by embracing and preparing for chaos.
Why does Chaos happen?
The seeds of chaos are planted by dangerous mindsets that might seem like positives in the beginning: faith, optimism & bliss.
In this context faith refers to a belief that all initial assumptions were correct.
It’s an unrealistic confidence in one’s own skills, thinking experience means the team has all the answers and there’s no edge case they may be missing. The truth is that no one can foresee every potential problem.
Good developers are always open to learning and overcoming their limitations.
Optimism is general feeling that the easiest, most fluid path will cover 99% of situations. It’s a mistake to assume that a basic implementation is enough to cover most scenarios.
Operating under the belief that nothing too disruptive will happen removes the incentive give to create functional contingency plans.
If ignorance is bliss, the reverse is true as well. Bliss here describes a cheerful lack of understanding of the technology stack, the project’s scope, and business requirements.
Every tool has strengths and weaknesses. Developers have to know those weaknesses to compensate for them.
These mindsets invite chaos into the development process right from the start. Left unchecked, they increase the risk of a major oversight.
There are ways for developers to stay on top of potential chaos without knowing exactly what form it will take. Start by prioritizing evidence over faith.
Turn the unknown into the known through a solid discovery. Best case scenarios are rare in software development industry; anything that can go wrong, will. It’s better to be over-prepared than caught off guard.
Don’t make assumptions without strong supporting evidence.
If no evidence is available, commit to a course of action as late as possible to allow room for change.
Practice “inversion thinking” during development. Game out the potential hazards ahead of time. What are all the negative things that can happen? How likely are they?
Brainstorming worst case scenarios provides the chance to create viable contingency plans.
It’s also a good idea to communicate thoroughly with the product owner about the impact of certain requirements.
Make sure everyone knows which options are riskiest. Provide a full risk-benefits analysis to guide product owners in making decisions about feature priorities and change orders.
Rolling with the Punches
Be alert for early signs of chaos and head them off at the pass.
Defensive programming is key. Test early and often. Every time a bug is found, write a test against that bug.
Knowledge is the currency of success. Have a clear understanding of the requirements before writing a single line of code.
Always understand one level below the level being worked on. Never stop learning. The technology steamroller is constantly moving, and it can roll over those who don’t keep up.
Finally, remember this: developers aren’t paid to write code (although they do). Developers are paid to think and solve problems. Don’t just patch based on assumptions.
Work through the actual problem to create a solution aligned with the products owner’s business requirements and stack technology.
A problem half stated is a problem half solved, so understand the actual problem from its roots before taking action.
Stay Alert, Stay on Schedule
Pessimism in development allows optimism in production.
Controlling for the mindsets that feed chaos leads to fewer and more manageable disruptions later in the game.
There’s always an element of chaos in software development, but the best teams know how to channel it into better software. Schedule your free consultation to hear our plan for your next project!
Guest post from a talk given on Sept. 7th, 2018
I want to talk about a tech entrepreneur who isn’t around anymore. He had a tech company and loved to tell stories. His first real viable product, his MVP, was that guy:
90 years ago a guy named Walt Disney came up with that guy. He was a true visionary. The interesting thing about Disney was that he made that success through animation, he made it through the parks, but he had a bigger vision. The epicenter of what he wanted to build was called Epcot. It certainly wasn’t the Epcot of today. It was the experimental prototype community of tomorrow.
Think back to the mid-60s. There were riots, cities were kind of falling apart, there was racial strife, there was economic strife. Walt Disney wanted to create something significant to give to the world.
“We’re going to build an amusement park and it’ll attract all the people and it’ll be a huge success. And right in the middle we’re going to build this thing- this community of tomorrow. We’re going to address housing and food and energy and transportation and education, and we’re going to disrupt all of those things.”
That was in October of 1966, and unfortunately in December of 1966 he died. All that inertia, that energy, fell by the wayside, and the company didn’t know how to follow his dream which is how we ended up with the Epcot we have today.
The biggest things Walt cared about came down to basic needs. He wanted to disrupt how we distribute basic needs. That’s what he was trying to do with Epcot – and 52 years after he died, technology is finally catching up with the visionary things he wanted to do back then.
3D Printed Housing
Over a billion people on the planet are housing insecure or homeless. ICON, a company out of Texas built this house in 24 hours for $10,000 dollars, and it’s a three room home. ICON thinks it can get the price down to $4,000.
For comparison, the Commission on Homelessness did a study about what it costs to leave a homeless person on the streets and they found it’s over $30,000. Putting them in an assisted living costs $12,000 a year. Now these homes could be $4,000 plus upkeep.
The amount of sun that hits the Earth in one day is ten times more than humanity uses in a year.
We’re only a few Moore’s Law doublings away from solar energy becoming a major player, and once we it’s cheaper to plug in than fuel up people are going to buy in on a larger scale. I think we’re close to that tipping point.
People say water is scarce, but two thirds of the planet is covered in water. We don’t have a water issue, we have a salt issue. Guess what gets rid of the salt? Energy.
We already have desalination technology, in fact there’s a new low-energy desalination process coming out of MIT. People think it’s expensive, but it’s not if you have abundant energy and energy is on its way.
The other thing Disney really wanted to tackle, especially back in the 60s, was transportation. Google and GM are launching autonomous fleets next year. We’re almost there on a technology side. Now it’s about our safety and comfort levels and public policy.
Disney’s dream of the monorail is being realized in Hyperloop, which can run from Orlando to Miami in 26 minutes. Once that’s finished you’ll be able to take your autonomous car to the Hyperloop and be safe as safe can be.
Looking a little further, Space X’s Big Falcon Rocket is promising travel to anywhere in the world in less than an hour.
Global communication networks
Companies are putting up constellations of satellites to provide- instead of hard wired internet access- global satellite-based Wi-Fi. Your phone work as well at home or in Antarctica. This is more than a convenience.
Half of the world doesn’t have internet access. That’s the digital divide we talked about back in 2000. We have it today, and it’s the developed world versus everyone else.
Imagine if you brought 4 million new minds – customers – onto this global platform. Imagine the problems they could solve and the things they could learn.
These technologies aren’t in the distant future. They’re all projected within the next 5-7 years, and they’re going to converge with each other to change how we distribute resources.
That was what Walt Disney recognized, that through technology we really live in an abundant world. We’re not suffering from a lack of land, we’re suffering from an inability to distribute.
For me that’s the most exciting possibility created by these disruptive technologies: having a connected world where we’re all sharing and listening to each other (or at least learning more).
Is your company positioned to take advantage of market-disrupting technologies as they mature? Set up a free consultation to evaluate your digital strategy and prepare for the world of tomorrow!
Tension is building in the business world. On one side lies mounting evidence that implementing artificial intelligence can rocket a business past its competitors. On the other, executives worry their company isn’t ready for AI.
Preparation is the difference between success and a wasted investment, and seeing high profile losses deters leaders from pushing forward with their own AI initiatives. That puts them at a disadvantage versus data-ready competitors.
A low-stress way to resolve this tension is to pilot one of the more “entry level” AI technologies. There are several relatively simple tools which can be used to build confidence in artificial intelligence.
A Cautious Approach
72% of companies feel AI is a major competitive advantage. It’s mostly larger companies moving to adopt, though. 40% of organizations with more than 500 employees are launching chatbots or intelligent assistants this year compared to about a quarter of smaller companies.
Why is there such a gap when so many recognize the potential of AI?
Small and medium companies hesitate for several reasons:
- Feel the technology isn’t enterprise-ready yet
- Security and privacy concerns
- Think cost is too high
- Not enough success stories
- Too complicated to implement
These fears reveal a common misconception about artificial intelligence. Adopting AI doesn’t have to mean a complete overhaul of existing tools and workflows. Companies can start small and integrate gradually to grow into a process that works for them. Here are some entry-level artificial intelligence tools to get the ball rolling.
Virtual assistants are probably the easiest form of AI to use. There’s a very low bar to entry since many companies already have them available. Virtual assistants often come bundled with popular enterprise software and productivity tools. Cortana, Siri, Google Assistant, Alexa, and similar assistants require little to no setup. They can be learned in a single training session or even by using the software’s tutorial. In fact, nearly half of American adults use virtual assistants for personal business.
Virtual assistants vary, but common applications include:
- Voice to text dictation
- Team collaboration
- Calendar management
- Email management
- Travel planning
- Small scale research
- Data analysis
Right now, virtual assistants are most regularly used in the IT department. That’s an unfortunate waste of resources. Integrating these tools into daily operations cuts down on tedious administrative tasks and improves the efficiency of interdepartmental workflows. For example, when used to plan travel or meetings, the assistant updates all relevant calendars, so everyone is on the same schedule.
Since it’s likely a company already has virtual assistants available, putting them to work is mostly a matter of spreading awareness. Hold training to generate excitement and demonstrate the possibilities. Guide mid-level managers in integrating assistants into their existing workflows and make easy-to-navigate resources available for reference.
Conversational interfaces make a huge difference when they’re customer-facing, too. Chatbots can handle a flood of incoming customer inquiries without making customers wait on hold. They’re available all day, even after business hours, and are unfailingly polite no matter how frustrated a customer is. Chatbots typically transfer difficult issues to a live agent, but in practice they can handle 80% of routine questions unassisted.
About 45% of global internet users actually prefer a chatbot to a live representative as a first point of contact. They’re more willing to engage with bots than humans early in the purchase cycle, when they’re researching options. No-pressure information provided by a chatbot can inspire conversions down the road.
As an added benefit, chatbots power future artificial intelligence ventures. The data they provide on what customers want and need feeds the sales and marketing process.
There are a number of online bot builders, but those tend to be little more than toys. Security can also be an issue if the builder doesn’t understand the larger technical pictures. It’s safer- and surprisingly economical- to have a chatbot specifically built for the company website or social media page.
Marketing Email and Text Optimization
Marketers spend as much as 35 hours a week crafting and testing emails, and for good reason. Emails and texts have high ROI potential. They’re a major driver of business with low overhead. 61% customers like to get relevant emails from brands, and artificial intelligence helps create that relevance while reducing the time humans spend on the more tedious aspects of the process.
Intelligent email optimization software can generate personalized messages triggered by specific customer activities that indicate interest. They use tailored subject lines, internal content, and timing designed to catch each customer at the ideal spot in the purchase cycle. Artificial intelligence is the driving force behind the 3 year high on marketing email and text open rates.
While email optimization isn’t as simple to put in place as chatbots or virtual assistants, it’s an excellent choice for the early stages of AI adoption. It can demonstrate its value clearly and relatively quickly. Take Sprint as an example. Sprint began using artificial intelligence to guide their text interactions with customers. With targeted, relevant messages the company was able to reduce the number of texts sent to customers while improving base SMS marketing returns more than six times over.
Leading from The Front
Most importantly, have executives lead by example with these early tools. High adoption rates are a huge part of making any tech project work. If leaders show commitment to the artificial intelligence tools, their enthusiasm could make the difference between success and failure.
Ready to explore how artificial intelligence can benefit your enterprise? Set up a free appointment with one of Concepta’s developers to find out what your options are!