How to succeed at technology projects

Most technology projects fail (some estimates say 80%, in the government context). Luckily, success is not random: failures happen for very predictable reasons. It’s often because we:

• Jump to solutions without testing them out
• Don’t recognize the constraints we have to meet or
• Fail to solve a real problem for the people we’re trying to help

Where AI Helps, and Where It Doesn't

If you know exactly what you want, AI can get you from point A to Point B quickly. However, it cannot tell you what you, your organization, or your users want.

AI Workbench guides you through an end to end workflow that asks the right questions and helps you figure these things out. In each activity, you'll learn what a successful technology project looks like, and how to effectively use AI to speed your project up.

Start with the outcome

You may already have an idea of what you want want to build: a new website, an AI assistant, or a replacement system. But underneath that solution there is probably an even more important idea: what is the change that you want to see as a result of this work? Why does this change matter, and why would we spend our time, money, and energy on it?

Defining a clear outcome gives you a standard for every later decision. Once we have a sense of the outcome we're aiming for, we have can look closer at all the ways we might achieve that outcome, and test our ideas to see if they are successful.

In this activity we'll take a first pass at defining the outcome we want to see so that we can stay on track for success by adjusting course early and often.

Further Reading

• Create a vision - Turns research and problem statements into an ambitious, measurable, outcome-focused vision.
• Success metrics - Defines quantitative and qualitative measures, data collection, ownership, benchmarks, and review cycles.
• Measuring the benefits of your service - Connects baselines, service improvements, costs, benefits, strategy, and value for money.
• Understanding and meeting policy intent - Converts policy intent into problem statements, target outcomes, measures, and baseline evidence.
• B.C. Digital Code of Practice: Focus on outcomes - The first principle recommends clear outcome statements, meaningful indicators, and transparent decisions.
• Alberta Digital Service Standards - The third principle "Focus on Outcomes" defines the value of the technology based on which end user outcomes it improves.