The idea for this article came from a dream I had this morning, where I was interviewing with a company and I asked one very important question...."Does your organization take time to do research, find data gaps (and seek to fill those gaps), look for opportunities to innovate with the data they have, while working on regular projects?" After I had asked this question to the first person I was interviewing with, I then was passed from one data analyst to another. Two analysts had given me some sort of excuse as to why they couldn't answer the question and the third said something like "Well, I don't have time to answer your question...I am very busy...and then he went on to describe an internal political matter that caused him grief." Basically, the answer was that this company did not take the time to really work with their data...but instead became paralyzed with what they already had and the workloads and inner politics surrounding it.
If this company were real, and not a figment of my imagination created in my dream...I would suggest this to them. To be competitive as an organization and to make work more interesting and vibrant, there needs to be dedicated time made for data. In the various organizations that I have worked in...I have seen several practices that have helped a company be successful with this...for example:
- Engage in projects that identify data 'gaps'. Reach out to your various organizations...find out their needs. Find out what the data answers for them and what it doesn't. Find out what they'd really like to know that their data is not answering for them now...and seek ways to fill these needs.
- Look for data overlaps and data 'excess'. Sometimes, whether its through reporting or even data sets that are sitting in various repositories, overlaps and data 'excess' can be created which can cause needless slowdowns,workflow inefficiencies, time waste and data space waste. A project to identify overlaps and data 'excess' can be useful to deal with this. One project I did, for example, was to identify all the reports created at an organization and determine which reports were being used and which were not. This project helped because we were able to identify which reports were not being used so they could be eliminated and it created an understanding of all the different reports being created that could possibly be used across the various teams at the organization.
- Take time to delve into the data and find innovative ways to stretch it. One project I did once at an organization did this very thing. I was tasked to understand all of their data from the various sources and how it could be used for analytics and modeling. I went the extra step to teach them how to create variables from what they already had so it would enhance what they could learn from their customer base. Further, I identified third party variables that were being paid for and found a suitable public source that they didn't have to pay for. This effort really helped with the analytics and modeling that I was tasked to do after this project.
- Take time to understand the third party data you have purchased. I once worked at an organization that had purchased various different third party data and when I asked what people knew about it, I didn't get straight answers. What that told me is that they had purchased data, but didn't really know if it was useful or not. I proceeded to test a given set of this third party data for a project I was working on and found it extremely useful to identify target populations for mailing (I was a marketing analyst). Because of the success of the test, these variables were used and saved the campaign I was tasked to save. And all it took was a little research time and trial.
- Look at improving processes that access and read in data that is being used for reporting and other processes. I once did an interesting job at an insurance company where I was tasked to improve coding for various reports being created at the organization. I was asked to look for coding inefficiencies as well as ways to improve the coding. What this did, when done successfully, was improve processing time and create increased automation for the work they were doing. I guess you could call this 'streamlining' and I found it to be a very useful practice in making things better.
Besides opportunities, I also found certain things held back organizations from doing the above. And this speaks to the dream I had. For example...
- Heavily siloed analysts that work on very specific things...that may not get the chance to work with other parts of the organization. While this sometimes can't be helped, I found it useful to be engaged in cross-team projects with various data analysts across the organization...to work on projects that affected the entire organization.
- Company politics that focus on short term vs. long term goals. This can be very stifling to an organization. If all your focus is on short term financial goals and 'putting out fires', you are neglecting long term growth, competitiveness and steadiness/stability. Recognizing that you have politics that hold you back can be very challenging as well...especially when people's reputations can be affected.
- Having an overabundance of work and overburdening your analysts can also be a source of stifling to innovation. In an age where many companies are trying to cut costs and divide workloads among fewer and fewer analysts, while this approach can help with short term cost benefit, it will not help with long term growth and being competitive. A balance should be found where workloads become manageable and that analysts are given some free room to innovate. It will make their jobs more enjoyable and lead them to be more productive with the work they are already doing.
In my mind, if you don't take time to innovate and improve your data...as a company you become just like hamsters running in a wheel. It looks like you are working, but you are not really getting anywhere. And, you tire out the hamsters (your analysts) who probably want to do more with their careers than just round around in circles for you.
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