The missing piece of the Agile puzzle
How to Get the Buy-In Needed to Move Your Project Forward
I spent over a decade in public service building out the next generation of big data analytics, security tools, and ...
I spent over a decade in public service building out the next generation of big data analytics, security tools, and high throughput data processing systems. Two things always slowed me down when I started to work on a project:
- Figuring out the right people to work with.
- Convincing people they should prioritize helping me work on the project.
At BMNT, we’ve figured out how to quickly get past these two challenges. First, talk to everyone in your organization to understand each person’s biggest problem, the thing that keeps them from being successful, and then organize that information into groups of similar problems. We call these groups problem topics, and they clearly show the prevalence of each group of problems to convince people to help out on a project. Problem topics are also great when looking for the right people to work with as they contain all the people that expressed the problem.
This discovery process can be done simply by talking to people one on one, up to about 50 people. We have found 100 people is pretty much the maximum you can gather data from in this way. To help us scale into the thousands of people, we created an AI to gather and organize that data into problem topics for us. This product uses a chatbot trained to understand people’s problems to gather the data.
A problem topic is comprised of three attributes:
- Definition - what the problem topic is about.
- A two-sentence summary of the group of problems within this topic
- The problems themselves
- Population - who cares about this problem topic
- The list of people who expressed problems that fit within this topic
- Prevalence - how important this problem topic is to the surveyed community
- The percent of the surveyed community that experience this type of problem
When analyzing problems from across a community, problem topics help:
- Gain buy-in: they get data that proves how important a given problem is to solve.
- Get started: you have a list of people to collaborate with + help you push through bureaucracy.
We saw these two benefits alone save three months of labor-intensive interviewing and analysis to achieve a comparable end result for one of our intel community government customers. This agency focused on the entire user base of a major software platform to gather and analyze problems these users experienced and identify the people they needed to start solving their most prevalent problems - in just one week.