Improving Higher Education Through Data with David Niemi

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Episode Summary

David Niemi loves higher education. So much so that he’s spent his entire career involved in it. From an early age, David recognized that there were better ways to help students and learners achieve their goals, and he’s been on a mission to make that experience better ever since. Throughout his career, he’s been a teacher, student, EdTech leader, professor, and analyst. David perfectly straddles the line between technology, data science and education, which makes him well suited for leading Kaplan’s Learning Analytics division, as the VP of Measurement and Evaluation.

If a picture is worth a thousand words, then a data visualization must be worth far more than that - Dave Mathias

EdTech has come a long way in the last 20 years. But even today, David believes there’s lots of opportunity to do it better. He starts with a basic question: “If we actually built ed-tech that taught people something, how would we know if they’re actually learning anything?”

This is the foundation for David’s role at Kaplan. He’s looking past “completion rates” and “GPA” and looking at measuring the real skills that are transferred to the students. He’s focused on the learner outcomes, like getting a job, increasing their salary, and improving their lives and communities.

So what are the key metrics or questions should Higher Ed be focusing on? David boils it down to three easy points: Are the students learning something? What is the level of student engagement during the course? What are the measures of student motivation throughout the course? These are different than the typical metrics because they are collected in near-real-time and provide teachers with tailored feedback on each student that ensures they’re getting the right level of instruction at the right time.

A measure of learning should tell you what new skills, knowledge, ideas and concepts have you developed. Not how many courses you completed.
— David Niemi

David also shared some interesting correlations between how to successfully educate learners and how to run successful analytics projects. In both cases, you need start with the end in mind… For education, it’s

1) what do you want to do in your career?

2) What skills do you need to get there?

3) Which classes or programs will provide those skills?

This is exactly how analytics projects should work!

1) What does the business need to solve?

2) What data do we need to inform those decisions?

3) What techniques do we use to tease the answers out of the data?

We also talked a bit about David’s new book, Learning Analytics in Education which is a set of research studies focused on pairing education data with data science techniques to drive better engagement for students, whether in online classes or in-person.

The book is one of the first to look at these new EdTech platforms that allow for ongoing measurements of student progress. They investigate how they can use these new data points to help educators increase their students’ success. These educators can now harness data to personalize the experiences for learners, while improving overall outcomes at scale.

If you’re at all interested in this brand new space, we strongly encourage you to pick up a copy!

And thanks to David for coming on the show!

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More about David

Check out David’s book on Amazon: Learning Analytics in Education

Connect with David on LinkedIn: in/david-niemi-2630757

Follow Kaplan on Twitter: @KaplanNews


The Data Able Podcast is made possible by Beyond the Data

We are on a mission to help people like you become a champion in your organization for a more data-informed approach. Data science and analytics is critical, but getting real value requires building a culture that starts with you, is supported by executives, and trickles down to every person in your organization.

 
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Who is Driving Your Data Culture Transformation?

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There are several critical roles that are critical to increasing the maturity of your analytics. But the glue that holds it all together is the person we refer to as the Data Champion. You won’t see a job description for a “Data Champion”, but all organizations that have a strong data culture will have at least one, and likely more.

Data Champions are people that spearhead data culture within an organization. Sometimes they are an executive or senior leader, but often-times they’re the boots-on-the-ground people who are simply passionate about promoting and improving data-informed decisions for their organization. They may be part of a business team, data team, or technology team. They may be extroverts or introverts.

What does a Data Champion Look Like?

Data Champions are natural disruptors, communicators, and networkers who can establish, drive, and support a clear data-informed vision. Data Champions are made not born. You will often spot them because they will be seeking to start an internal meetup around a data-related topic or starting a data visualization competition or maybe they will be the person that is at other’s desk showing them how to approach a data problem. They aren’t necessarily the most technical person in the room. But they are most certainly the ones who are building communities, telling stories about the possibilities, and focused on embedding analytics into every corner of the organization.

These Data Champions will be present in an organization whether they have been sought out or not. Organizations with a strong Data Culture though will have more of these Data Champions and their level of empowerment and satisfaction will be higher.

What does a Data Champion do?

Data Champions play a key role in helping translate between the business and their area of the organization to help drive data-usage when making decisions. They engage with business and technology partners to ensure they are smoothly working together. Further, Data Champions will have relationships with other current and future Data Champions including those not within the Chief Data Officer’s direct area.

Data Champions are more than just translators though. They create vision, alignment and empowerment to the teams they support. They build energy and excitement for a data-informed approach. They are skilled at working with business leaders to build trust in the analytics solutions being built. And they constantly communicate the benefits that data can provide, the results that the organization has gotten from analytics investments, and they communicate the vision for the future.

Champions are Critical but not sufficient

Getting the organization moving in the right direction is obviously important. But doing so without executive buy-in will result in frustration, limited results, and lack of funding. Executives have to be part of the equation.

Similarly, moving forward without a technology foundation (quality data, storage platforms, reporting tools), and skilled analysts to dive into that data, will also result in limited results and frustration. The data team and technology must be a critical part of the equation.

Finally, it’s important to not that the best champions are ones that work themselves out of jobs. “Translating” between the business and analyst teams is critical in the early going. But think of the benefits if translating didn’t need to happen, and both teams simply spoke the same language. Reduced friction, reduced effort, and faster/clearer communication would result. The data champion only translates until they can get the teams talking in the same “language”.

Here’s a great video about how Data Translators are critical pieces, but are a stepping stone to the whole organization being data literate.

 
 

This article appears in a series of blog posts about Data Culture, Data Literacy, and why it matters for organizations to think beyond Data Science. If you liked this article, make sure to read the rest of the series:

Five Reasons Why Data Culture is Just as Important as Data Science

The Key Roles of a Data-Informed Organization


Beyond the Data is on a mission

We help high-performing individuals become champions for a more data-driven approach in their organization. We believe that data science is only part of the equation.

Getting value out of data requires building a culture that starts with YOU, is supported by executives, and trickles down to every front-line specialist in your organization.


 
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The Importance of Data Storytelling pt 2

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In this episode Dave and Matt continue their discussion on data storytelling. Good storytelling skills can be used for good and evil. One key is taking audience in mind, being ethical, and being transparent when framing the story.

 
Storytelling is useful, but it can sometimes take people too far away from the data itself
— Dave Mathias
 

Moving beyond verbal storytelling there is the same need for these principles to be applied in all forms of communication. This includes email and utilizing things like clear and concise subject lines and writing like a journalist will help ensure effective emails and other written communications.

There will be many episodes where we will touch on the importance of storytelling and other tips and tricks. Plus we are lining up some great guests that are compelling storytellers to share their tips.

If you liked this episode, then make sure to catch part 1 of The importance of Data Storytelling.

Until next week!

Resources & Links

Present Beyond Measure Podcast by Lea Pica

Mico Yuk, Data Storyteller - CEO of BI Brainz

Story by Data by Kate Strachnyi

Storytelling with Data by Cole Nussbaumer


The Data Able Podcast is made possible by Beyond the Data

We are on a mission to help high-performing individuals like you to become champions for a more data-informed approach in your organization.

Getting value out of data requires building a culture that starts with YOU, is supported by executives, and trickles down to every person in your organization.

 
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The Key Roles of a Data-Informed Organization

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Most people would all agree that data is a key go-forward strategy for their organizations.

As we discussed in a recent article however, there are some significant challenges that come with executing on that strategy. How do we overcome those? You need to embed analytics and data science directly into your organization’s culture.

There are three interlocking roles, each with some level of responsibility for making analytics work. The fourth and most critical role, the “Champion” sits at the center of these roles, driving alignment between everyone and driving successful change managment.

Over the next couple weeks, we’ll break down these roles in much more detail, but here’s a high-level overview:

The Executive Team

The CEO, CFO, CMO, CHRO, an the rest of the C-suite. When push comes to shove they need to support data initiatives, support the financial investment in the, weave data into the strategies of the organization, and ultimately hold the organization accountable to data-informed decisions and actions.

The Business Team

The many core functional areas of your organization. From human resources to sales to product to finance, the business team is critical to driving successful analytics. They must be on board and empowered to use data. Without this team informed, engaged and comfortable with data, then your amazing analytics outputs will fall on deaf ears, and the potential business value will be lost.

The Data Team

The extremely adept technical team who will be moving, storing, touching, analyzing, manipulating, and communicating your data. There are many roles within this broad category, but could include people like BI Developers, ETL Developers, Business Analysts, Data Scientists, and Report Creators. The key to their success is to turn them into key business partners, rather than basic order takers.

The Data Champion

The highly driven person or team at the center of it all. They are the evangelists that shout from the rooftops the importance of data for your organization. They “translate” how data can help the business, communicate it to leadership, and ensure the data team executes on the efforts. Data Champions are natural disruptors, communicators and networkers who can establish a clear data-informed vision. They create excitement and energy around data, and know how to influence the other three groups on how to execute.

These stakeholders together provide the pillars of support for an organization’s data culture. If one or more pillar is out of alignment, then the whole data culture is weakened. One pillar is not more or less important than any other. They each play a role in driving the data maturity of the organization and in-turn, the value that can be captured by analytics.

So what about your organization? Can you identify the people who fall into each of these groups? Are each of them in alignment with each other? What is the missing link that is holding your organization back from leveraging data effectively?


Beyond the Data is on a mission

We help high-performing individuals become champions for a more data-driven approach in their organization. We believe that data science is only part of the equation.

Getting value out of data requires building a culture that starts with YOU, is supported by executives, and trickles down to every front-line specialist in your organization.


 
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Stories from the Data Trenches with Liz Weber and Tessa Enns

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Episode Summary

Back in December, Dave and I had the privilege of doing a speaking event at the MinneFRAMA (Finance, Retail, Marketing Analytics) event. Naturally, we decided to try something different and tape a live episode with two of my favorite analytics professionals in the Twin Cities, Tessa Enns and Liz Weber.

It was truly a once-in-a-lifetime experience: Sipping coffee, and talking analytics with these two amazing women. The venue didn’t hurt either! We were in a huge room at the Minnesota Science Museum, with our backs against a wall of windows overlooking the Mississippi river. We learned a lot about how to make sure your analytics projects are truly successful.

Tessa Enns

If a picture is worth a thousand words, then a data visualization must be worth far more than that - Dave Mathias
I’m not working to fuel my technical skills, my technical skills are working to fuel the business challenges
— Tessa Enns

Tessa talked to us about “accidentally” coming into an analyst role at Cargill, being given a huge transportation dataset and being tasked with finding something in it. Tessa is the kind of amazing person who looked at this as an opportunity, and went right to work, learning the data, learning the business, and learning technical skills along the way.

What is so amazing about her journey is that she was able to build a strong relationship with the business, who now trust the data, find opportunities to improve, and know how to turn the numbers into action that drives real monetary value.

Tessa preaches an approach where analysts need to “lead with the needs, not with the data”. She says this helps the analyst understand the real problem and help solve it. She also recommends putting every insight into dollar terms that your business will understand. “I put the cost savings or cost impacts right at the top of every dashboard”.

Liz Weber

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Take some time to understand the business processes that create your data. You will be able to understand your business teams and tell better stories that drive change
— Liz Weber

Liz talked to us about a highly complex pricing challenge that her VP faced a number of years ago. The team was going through a major transition, and had invested a huge amount of money in their business. The VP wanted a dashboard to start monitoring whether this transformation was going successfully.

Liz started with the end in mind. Learn about what the leader wants, where they’re trying to go, and what the key measures of success really look like. She then sat down with the IT team, and the business teams underneath this VP. Making sure that everyone had a voice in the project was mission-critical to make sure that she 1) had the right resources, 2) had everyone moving in the same direction, 3) made the solution better than just her own ideas. It also helped with adoption, and making sure that everyone actually USED the end product.

What she learned from this project was that your leader/sponsor matters. If you don’t have the right sponsorship, it doesn’t matter how smart you are, or what kinds of technical knowledge you possess. You need to make sure you’re aligned to leaders who are committed to doing something with the outputs you produce.

Resources & Links

Tessa on LinkedIn: in/tessa-enns

Tessa on Twitter: @TessaEnns

Liz on LinkedIn: in/lizweber2

Twin Cities Tableau User Group

Twin Cities Alteryx User Group

Minneanalytics

Cargill

UNFI Supervalu


The Data Able Podcast is made possible by Beyond the Data

We are on a mission to help high-performing individuals like you to become champions for a more data-informed approach in your organization.

Getting value out of data requires building a culture that starts with YOU, is supported by executives, and trickles down to every person in your organization.

 
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