Boost Midwest Coffee Corner - November 2020


Conversations on Data Management

Welcome to the Boost Coffee Corner! Every month we’ll highlight a member of our team to share with you some of their tips & tricks in optimizing operations to elevate results! In this meeting, we discuss The Moving Target of Data Management. If you prefer to listen, you can find the video below along with the transcript for your reading pleasure!


The Team

This episode of the Boost Coffee Corner features perspectives from Marie Stacks (President), Justin Murdock (Project Analyst), and Rebecca Preston (Project Coordinator). To learn more about the team, please visit our website.


Marie Stacks 0:00

Hi! And welcome to the Boost Coffee Corner. Each month we will gather to share our tips and tricks and our clients' favorites for different topics. This month we're going to talk about "The Moving Target of Data Management", looking at how you collect your data, how you share your data, and really what does data even mean sometimes. So, I am joined today with several of our team members. So Justin, I'll hand it over to you to introduce yourself.


Justin Murdock 0:32

Hello, everyone! Thanks for tuning in. I am Justin Murdock. I'm a project analyst with Boost Midwest, and I'm really excited to talk about data today!


Marie Stacks 0:42

We've got Rebecca as well with us today - Rebecca?


Rebecca Preston 0:46

Hi, everyone, Rebecca Preston. And I'm with Boost Midwest as well. And I am really excited to talk about data with you all today!


Marie Stacks 0:58

Awesome. And I'm Marie Stacks. And we are here for our Coffee Corner. I think considering it's the afternoon, I'm probably - Oh, no, Justin's drinking coffee too! [laughter]


Justin Murdock 1:08

[showing thermos to camera] I've got a little iced coffee going on. [laughter]


Marie Stacks 1:10

So we definitely are coffee fanatics. But probably more me than anybody. To kind of kick us off today... Justin, I love this question. When you begin a project that you know will involve heavy amounts of data and data management what is the first step that you go for? How would you answer that one?


Justin Murdock 1:32

I think that's definitely the most crucial step, because the way you start a project determines how you're going to carry it through. I like to think of it as creating a detailed plan, making sure that you know the who, what, when, where, why, before you actually even try to create any technical tools for data collection or management. Because the way that you answer those questions is really going to impact the way that you design your tools, your database, whatever processes you may put in place. And then while you're answering those questions, I like to try to engage as many stakeholders as possible. Because you never know what answers they will have that will have big implications later on down the line.


Marie Stacks 2:11

That's so true, especially with stakeholder engagement. I know, Beca, you've had quite a few pieces of projects that you've worked on that have involved different stakeholders. What do you think? I mean, what are pieces of the data puzzle that you see as being some of the most valuable or most important to collect?


Rebecca Preston 2:29

Well, I think at the end of the day, that - the cheesy statement is data paints a picture. And how are you going to paint that picture? You know, like Justin said, who wants to look at the picture? Why are they looking at the picture? What's their buy in? And what are we evaluating? What are the little bits and pieces of that picture, you know, the clouds, the happy clouds, the happy trees, who's listening, who's watching, and I think the stakeholder buy-in is a major, major one to pay attention to. And then accuracy of your data. There's so many different data points that you pull into on a project. And not all of your stakeholders are interested in the same data points. So I think it's really important to figure out what their buy-in is and what picture you want to paint for them.


Justin Murdock 3:25

Absolutely.


Marie Stacks 3:26

Such a good point. And I think it's funny - we have one of our questions that was sent in is, “at what stages during the project do you share data? And in what ways?” And I think you're absolutely right, it depends on the stakeholder. It's who you are engaging. Your board of directors may want a quarterly statement. And they may want a summary only. You may have some members of your board that want a very specific, detailed part of that. And then you've got your operations teams. And I think, you know, we interact a lot with that operations part of a company or a nonprofit. And, getting the grant project up and running is one thing, making it sustainable and operational is another. And so I think those are all very different sets of data. And so it's kind of fun that you know, especially our team, we get to kind of play with each of those pieces.


Let's see, what other questions do we have here? Here's a fun one, kind of along the same lines. How do you decide what information you can collect or should collect?


Justin Murdock 4:27

Yeah, I think again, it goes back to like Rebecca was saying, it goes down to what picture you're trying to paint and what picture needs to be painted for different audiences. Who's going to look at this picture? So it definitely depends on your project. From a research standpoint, it really depends on your research questions, and then consequently, what specific objectives you need to measure against to see how you're progressing in your project. And then when we're talking about grant management and like we so often do a Boost, it really depends on all the information that your funding organization wants to know. So you need to make sure you're collecting all that, and sometimes that involves reading between the lines. They may ask for one thing, and to determine that thing, you need a different piece of information. So it's definitely a process of looking at all of the possible things you may need and getting the steps in place to collect those.


Marie Stacks 5:22

Yeah. So true.


Rebecca Preston 5:25

I think with that too, your information and data that you're going to share with your grant management, or, your grantee- grantor [laughter] is probably most of the time different than you're going to share with who's involved in the program. Which I think it's important when you're managing your data to include all of those subsets. Instead of having two different documents or two different programs, I think it's important to include it into one, even though you're splitting up the data into maybe two reports, or three reports even sometimes can happen.


Marie Stacks 6:04

That's such a great point, I know that we constantly are creating reservoirs of data, for lack of a better term. And I think it's really fun to kind of take that reservoir and pivot it as many ways as we can to see, okay, what are we playing with here? It's almost like putting a Rubik's Cube together and figuring out - what side are we on? [laughter]


But I think too, I mean, some of the best practices and mistakes that we've seen along the way, those might be fun things for us to share, as well. So, who wants to take a first stab at a mistake you've seen that we maybe could avoid in the future? I know, I've got one off the top of my head that I could go with.


Justin Murdock 6:43

I want to hear yours, Marie!


Rebecca Preston 6:44

I was about to say! [all laughing]


Marie Stacks 6:47

Funny enough, I think, on that whole idea of the reservoir, a lot of times, we don't begin with the end in mind. Not necessarily us, but our clients, or some of the folks that are getting into grant management initially, or project management even. They start with just collecting what they see on the surface, and not necessarily starting with - Okay, what do we need to end with? What are we looking to actually report from a performance standpoint, or what does our grantor actually want us to tell them at the end of this? So beginning with the end in mind is usually what I see as being the biggest thing that's missed. Unfortunately, when you do collect too little on the front end, you end up having to almost restart, sometimes, your entire project, which means you're either going back to recollect data, or you're going and having to double your output on outcomes. There's a lot of different implications to that. So I think, beginning with the end in mind is the thing that I see as being a potentially really strong best practice to avoid that mistake.


Justin Murdock 7:48

Yeah, I totally agree. And I think that also ties into the idea of really carefully planning the entire data collection aspect of the project in advance and not trying to rush into things. Because a lot of times, you may feel like you're saving time at the beginning, but when you have to redo it all, you're certainly not saving any time there.


Marie Stacks 8:08

Oh, so true.


Justin Murdock 8:09

I like that phrase, "beginning with the end in mind".


Rebecca Preston 8:11

Absolutely. Well, go back to a picture. You know? You have an idea when you start drawing a picture, but you already have the end in your head. You have that goal objective in your head. My thing is to not assume your data collection tool is foolproof. So whether it's Google Docs, Excel, etc. I like to double and triple check, because I like to think I'm a professional at Excel, but that's just when you go back and you added an X when it should have been a Y, or there's a parenthesis instead of a comma. I think it's really important to go back and go through and have an extra set of eyes to go through your data collecting tool as well, so you know that your data is correct.


Justin Murdock 9:05

Very good point.


Marie Stacks 9:06

Yes, I was just about to say. I definitely send all my stuff to you guys and say, "Hey, can you double check that I didn't miss this?"


Rebecca Preston 9:12

"Can you be my eyes?"


Marie Stacks 9:14

Be my second set!


Marie Stacks 9:16

But I think that's such a valid point. It's data validation. A lot of times we have to create almost like our self data validation. I know a lot of people call them audits, but I personally don't like that word. I like to call them quality checks. So you're always subject to a quality check. But I think you know, Beca, you're hitting on something really important, and it's the data validation piece. And I know, Justin, you do such a wonderful job of it. What do you guys see as being potential ways to help with that - that QA, quality process of your data?


Justin Murdock 9:51

Yeah, this definitely ties in. I like the idea of getting different eyes on it and going back to getting stakeholder engagement. Accepting that we're not the experts. Your tools aren't foolproof. A crucial piece of data validation is to make sure that people, if you're gathering data from people, that they understand what they're answering, that they understand the tool that you've provided. And sometimes that's not necessarily the case. So you have to make sure that you've written things in a way that they are understandable, not just to you, but to everyone else, as well. So making sure that the data that you have actually means what you want it to mean, or what you think it means, and a lot of times that takes getting outside perspectives or putting it through a bunch of different types of analyses. Definitely not a simple process.


Marie Stacks 10:40

So true. What about a checklist? I know, I'm the queen of my top six every day, but I also live and die by checklist. Where could we use a checklist? I mean, I know personally, I use one just to keep myself on track.


Rebecca Preston 10:55

I think that you use it throughout a program process. So you're starting a program, you have the end in sight. And you have checks and balances throughout the process. You start with your introduction and your community stakeholders. You get everybody together. All right, let's double check, what do we need? What do we want? Alright, we started the process. We're six weeks in, let's check and see if what we're doing is effective and accurate. And then, you know, you start doing your quarterly reports and everything like that. I think it would be super beneficial to have a Marie checklist, you know, a week or two right before [laughter] quarterly reporting. I think the checklist thing is just- it's crucial. A lot of people call it evaluation, if you want to pull a buzzword there... I'm obsessed with double checking things. [all laughing] I just, I think it's important. I don't think there can be too much checking.


Marie Stacks 12:01

I was gonna say, I think at some point, we all forget one thing, right? It's like the checklist is what keeps us on track to some degree. So it's kind of like your project plan, but at a micro scale.


Justin Murdock 12:11

Yeah, and just looking at the data every day, I always make sure that I have this checklist of points that I notice- Hey, is this one out of whack? Just being able to to eyeball it, and you're right. It really alleviates a lot of the issues down the line if you have your checklist of problem places that you know to look for.


Marie Stacks 12:30

Yeah, absolutely. We could do this all day every day. [laughing] But it might be kind of fun for us to kind of go through some of the things that we enjoy with our clients on the project management and grant management stuff. I think for me, personally, I love being able to take a client's project, put it into actionable steps, and watch it transform what they're doing. I also love helping them reach their goal. But I think being at that day-to-day level sometimes means that we get to also help them fix things. So I think that brainstorming, that problem solving that we get to bring to it. I think our whole team is really good at that. So it's really fun that we all get to collaborate with others to do that. What do you guys enjoy about it?


Justin Murdock 13:19

Yeah, In a similar vein, I really enjoy learning new things. And I enjoy helping our clients learn new things about their projects, about their clients, or about their grants, or any of the above. So I enjoy being able to take information and synthesize that and help others learn more about their processes.


Rebecca Preston 13:43

Yeah, I think teamwork makes the dream work. [laughing] Collaboration and, I think for me, growing. Growth for me personally and professionally is learning new things like Justin said. And as long as I'm learning new things, I'm going to be able to do bigger and better things every day.


Marie Stacks 14:03

That's so well put. Awesome. I’m so, so glad we could share a little bit of our knowledge here today with our Boost Midwest team. Justin, Rebecca. Thank you guys so much. And from all of us here at Boost, keep on data managing!