Priorities in Handling Data and Getting Buy-in

In December, Data Expert Erin Prinster wrote about best practices on harnessing your data in the launch of her first, Ask Erin column. We received a number of responses. Here are her answers from some of the questions posed.

Q: Erin, do you have any advice on training tools available for operational managers who don't have experience in collecting and analyzing data to create process efficiencies or cost savings?

A: Some operational managers might not have experience in collecting and analyzing data to create process efficiencies and cost saving efforts. Yet, there are times when that isn't the issue. Sometimes, the experience is there, but lack of tools, knowledge of priority and expectations, or maybe even reluctancy is the culprit.

While analysis might not be a day-to-day duty for the operational managers, I agree it is a piece of the role they are expected to do from time to time. For those managers who want to have a better understanding of data management and analysis, there are a number of online tutorial tools, such as, Linkedin Learning, and (Python classes). As I go through my day to day I look for additional learning avenues myself and always have our members questions/comments top of mind. 

The bottom line according to this Forrester blog post on data literacy, is that better training leads to greater awareness, higher-quality data, and more accurate analyses. Employees recognize that it’s not just a matter of pushing any button but of capturing the data needed to make better business decisions and drive better business outcomes.”


Q: Erin, I am a numbers person, but the amount of data available to us these days can be overwhelming. What is the easiest way to turn data into actionable information? Can you recommend a way to start? Is there any low-hanging fruit? 

A: I agree, the amount of data can be overwhelming!

In my experience the easiest way to start is taking a look at your goals for the year, highest priority first. If you think your highest priority could be broken down into sub goals to make data analysis easier, by all means, do it. Divide and conquer!

Turning data into actionable items can be tricky too, sometimes we don’t know what we have until we get into the data and really start mining data. We might uncover something very valuable to our organization, it may or may not tie back to our goals, so we need to make sure we are always asking questions.

Understanding what our data means and how data can guide us to make decisions is very important.

There is absolutely low-hanging fruit in data.

I think often, we start kicking over rocks knowing data can be overwhelming that we miss things we can take care of very quickly. If we can knock that low-hanging fruit out of the way, that task could lead to making further analysis a bit easier.

For example, your existing customers. Data can tell us how to maintain existing customers, which is an easier task than gaining new customers.


Q: Data is absolutely our friend and is beneficial to every company. However, it can be challenging getting buy-in from the people you want to use the data, whether it be they don’t understand or they mistrust the information. Do you have any advice or insight into how to encourage reluctant users? 

I believe the best way to handle a reluctant user is to have an open conversation with the user. Ask the questions, “Why do you mistrust the information?” or “Do you need additional help understanding the information?” The majority of the time, it is the latter and it is difficult to admit the misunderstanding. Misinterpretation of information happens but having someone (that users manager preferably) that can peel that layer back and send the right person to help matters. A person that understands the information well enough to explain and teach it back to anyone, in any role, twenty different ways is usually the analyst.

Do you need some advice on managing or interpreting your data? Ask Erin. Contact her at or leave the question in the comments section.

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Erin Prinster

Erin Prinster

Erin Prinster is a Research and Data Analyst with more than 17 years of experience in analyzing the business needs of corporations and customers. She manages all phases of data collection and analysis for NAED research projects, including the application of standard, descriptive, and statistical methods for conducting analysis. Her passion is using data to provide insights into business performance, make recommendations, and create relevant practices and procedures to save companies time and money.