Listen to Les McKeown read this blog post:
As we've seen in the previous blog posts in this brief series, most, if not all strong leaders eventually reach a point where the quality of data they're receiving simply isn't good enough to make the important decisions involved in growing their organizations.
When they reach this stage, most leaders make an understandable, but ultimately flawed (and exceptionally expensive) mistake, and it's this:
They start designing their 'quality data flow' at the wrong end of the decision-making process.
What I mean by this is that the natural response to poor data is to start designing new systems and processes to deliver better quality data, making often huge investments in new software, building dashboards, installing robust data-gathering processes.
Which almost always ends up in an expensive misfire that can be described in one sentence:
Yea, we're getting quality data now, but it's the wrong data.
The right place to start is at the other end of the decision-making process - in the room (physical or virtual) where you actually make decisions.
Use these six steps to retro-engineer the right high-quality data you need to lead and grow your organization:
Identify the meeting(s) where the most mission-impacting decisions are made in your organization.
Pull together the agenda items from at least 6, preferably 8 or more of those meetings.
Separate out the high-priority / high-impact agenda items from the list. This will likely take the total number down to one-third to a half of the original list.
From those that remain, identify the 5 to 10 agenda items which, if you had had better data, you would have made better decisions which would have most positively impacted the organization.
Start building the infrastructure you need to provide you with that data.
Rinse and repeat the process from step 1 until you have high quality data for at least 80% of your recurring agenda items.
A 'by the way': As a strong leader, you're almost certainly thinking "I don't need to go through this exercise. I can tell you right now exactly what data we need to improve on." And you're almost certainly wrong.
Not to get too meta, but the exact same tendencies that made you overestimate the quality of the data you were getting in the first place (see the first post in this series) will also blind you to the data you truly need.
Try it - run the process with your top team and see what emerges. If you're right, you're right, and you'll be confirmed in that, if you're wrong, it'll save you a lot of time and resource in building expensive, but ultimately wrong data systems and processes.