I frequently compare #analytics to a marathon—one that isn’t one-and-done but a race that you keep running over and over. It’s a process that many organizations have successfully started—but have also frequently re-started and never finished.
In terms of #datastorytelling, there are a number of steps in the analytics process that must occur before we can even think about telling stories with the data.
1️⃣ We collect data on our business operations.
2️⃣ We prepare (transform, clean) the data so it's usable for reporting and analysis purposes.
3️⃣ We visualize the data in summarized reports and dashboards to help people monitor business performance.
4️⃣ We analyze the data to identify ways to optimize performance.
5️⃣ We communicate the insights to inform decisions (data storytelling).
6️⃣ We act on those findings to drive value for the business.
Today, 99.8% of companies are collecting data. Most of these organizations are also preparing reports and visualizing their data on a regular basis.
However, there's a significant drop off at the last mile in the race where analytics teams perform analysis, share their insights, and then implement changes to optimize the business. Note: The percentages I placed in the diagram are just rough estimates based on my experience (and they are probably generous).
As I consult with different companies, it’s not uncommon for me to run into analysts who are frustrated that they can’t do more analysis and data storytelling. They want to move beyond focusing on just the early phases of the race (data collection, preparation, and reporting), but they feel stuck with the reporting routine.
How can you fix this problem?
First, I would recommend automating and streamlining as much of the labor-intensive aspects of the first few stages as possible. If you can free up some cycles, that time can be better spent on the last-mile activities.
Second, rather than trying to fix everything that may be impeding your ability to progress through the entire analytics process, I recommend focusing on going the distance (end-to-end) in one or two targeted areas. If you can demonstrate the power of data storytelling with a narrower focus, you can use those wins to build momentum for expanding your analysis work and telling more data stories.
Organizations must finish the analytics marathon to get full value from their #data investments. If they keep restarting the race and only running the first portion, they’ll never deliver anything meaningful with their analytics tools. I encourage everyone to refocus and conquer the last mile to get those prized, hard-earned finisher medals!
What has helped your team to progress through all the stages of the analytics marathon? Alternatively, what causes you to continually restart the race and never cross the finish line?
In terms of #datastorytelling, there are a number of steps in the analytics process that must occur before we can even think about telling stories with the data.
1️⃣ We collect data on our business operations.
2️⃣ We prepare (transform, clean) the data so it's usable for reporting and analysis purposes.
3️⃣ We visualize the data in summarized reports and dashboards to help people monitor business performance.
4️⃣ We analyze the data to identify ways to optimize performance.
5️⃣ We communicate the insights to inform decisions (data storytelling).
6️⃣ We act on those findings to drive value for the business.
Today, 99.8% of companies are collecting data. Most of these organizations are also preparing reports and visualizing their data on a regular basis.
However, there's a significant drop off at the last mile in the race where analytics teams perform analysis, share their insights, and then implement changes to optimize the business. Note: The percentages I placed in the diagram are just rough estimates based on my experience (and they are probably generous).
As I consult with different companies, it’s not uncommon for me to run into analysts who are frustrated that they can’t do more analysis and data storytelling. They want to move beyond focusing on just the early phases of the race (data collection, preparation, and reporting), but they feel stuck with the reporting routine.
How can you fix this problem?
First, I would recommend automating and streamlining as much of the labor-intensive aspects of the first few stages as possible. If you can free up some cycles, that time can be better spent on the last-mile activities.
Second, rather than trying to fix everything that may be impeding your ability to progress through the entire analytics process, I recommend focusing on going the distance (end-to-end) in one or two targeted areas. If you can demonstrate the power of data storytelling with a narrower focus, you can use those wins to build momentum for expanding your analysis work and telling more data stories.
Organizations must finish the analytics marathon to get full value from their #data investments. If they keep restarting the race and only running the first portion, they’ll never deliver anything meaningful with their analytics tools. I encourage everyone to refocus and conquer the last mile to get those prized, hard-earned finisher medals!
What has helped your team to progress through all the stages of the analytics marathon? Alternatively, what causes you to continually restart the race and never cross the finish line?
