Ep 21 - Dennis Still - Analytics for Startups and Small Business

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“Big data, small data, medium size data. The real question is what you’re going to do with it once you have it.”
— Dennis Still

Dennis Still is a startup analytics expert. Where many analytics projects come from large $1B+ organizations, there are many startups and small businesses that need similar capabilities. How do small business compete and keep up? What kinds of challenges do these companies face, and how do they view their own relationship with data?

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Dennis has had a wide and varied career that didn’t necessarily start in data, but has taken him on a journey through various startups like When I Work, Gov Delivery, and his very own startup, Bigfoot Analytics.

Dennis has spent years working directly with entrepreneurs, figuring out what they need from their data, and delivering insights that drive exponential growth as they disrupt their various industries.

One of the biggest things he found through his time leading data and analytics, was that the questions that small companies are asking aren’t that different from what big companies are asking, just on a different scale. Revenue, costs, customer satisfaction. The key to his success was in being able to help his C-suite leaders identify their KPIs that would fuel rapid growth.

“Our CEO would throw out a number and 85% of the people in the room knew what that meant. It was the number that we used to drive the business forward”.

Despite being more nimble, Dennis feels like there’s a lot of opportunity still. "Who owns the data? How does it work? Who is going to look at it and do something with it?” A data-informed culture doesn’t just happen. It takes work from the analysts consistently pushing the metrics and getting the leaders to embed it into their communications.

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Ep 20 - Serena Roberts - Authentic Relationships That Build Analytics Success

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“Your job does not end when the analytics development is done. That’s when it starts.”
— Serena Roberts

Serena Roberts is a force to be reckoned with. She’s a mom, an analytics leader, a Tableau ambassador, and the driving force for two great local communities that she runs. That’s why we were so thrilled to get a few minutes of her time to talk about her approach to data, and how she’s become such a successful data leader.

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Like many of us, Serena didn’t start out on a path to be a “data person”. She kind of fell into it by accident… A happy accident that’s taken her on an amazing journey from “business professional” to data guru, to fearless leader of the Twin Cities Tableau User Group, and the Minnesota chapter of the organization, She Talks Data.

The first thing that you’ll notice about Serena when you talk to her is her passion for understanding other’s needs. She deeply cares about the people in her life, both professionally and personally. She’s also a data visionary. She sees where her organization needs to go and isn’t afraid to communicate that vision to others, even when met with resistance.

Serena talked to us about her time at Capella, and reflected on some of the lessons learned while working for a well-established and relatively “analytics-averse” organization. “I was the unpopular person pushing new ideas”. “We were really trying to change human behavior, one sales rep at a time”.

“I saw such a need for analytics and data that no one was looking at. I was the unpopular person pushing new ideas and challenging the status quo””

The more you talk to Serena, the more you realize that it’s HUMANS that drive her, not the DATA. For her, it’s all about helping individuals use data in their day-to-day jobs. Enabling those fundamental data literacy skills that empower a business person to make a better decision, communicate more effectively, or answer a question faster.

“People focus on technology and process… and they heavily underestimate the change management aspect of the work we do as analysts.”

Change management is about changing human behavior. That’s the hard part. But the data community is lucky to have people like Serena driving their organizations to a more data-informed culture.

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Jeff Sloan - Better Analytics through Product Management Principles

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“The best analysis for YOU might not be the best analysis for your USER. Make sure you think about the outcomes that you’re trying to drive.”
— Jeff Sloan

Today, on the podcast we’re trying something a little different. For those who may not know, Dave has been travelling through Africa and Europe the past 2.5 months as a part of a program called Remote Year.

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During his time in Cape Town South Africa, Dave was introduced to our next guest, Jeff Sloan who is also a part of Remote Year. Jeff is a self-prescribed Data Product Manager and they thought it would be fun to try recording some of their conversations.

They headed over to a local coffee shop and set up the mic and started chatting about data, business intelligence, product management and how these disciplines are starting to intersect.

If you hear banging dishes or cars driving by, feel free to imagine sitting outside sipping latte’s on a lovely warm day in an open-air coffee shop in downtown Cape Town, South Africa.

So, what is a “Data Product Manager”, exactly?

According to Jeff, this role is responsible for thinking about the data infrastructure of the entire organization, mapping out the flows, sources, and storage platforms for both internal and external data. It’s the first step in empowering things like Machine Learning, AI, and A/B testing across the organization.

 
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Jeff loves data, but he feels like many of the traditional ways that organizations use data and analytics today could be even better. That’s why he’s so interested in bringing product management concepts to data to deliver more value and better, more integrated insights. Product management tools like SCRUM, backlog grooming, and user experience can all play a role in driving more value.

“It’s important to understand where your [internal or external] customers are coming from. The more we can understand what they need and how they need it, the better we will be as data people… We need to take them along on this journey to using data.” How do we do this? Jeff recommends starting with the business question and then working backwards from there, in an iterative and agile way. This will ensure that the insight/analytics produced meets the needs.

Thanks for sitting down for coffee, Jeff. And good luck on the rest of your Remote Year travels!

More about Jeff Sloan

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5 Things Executives Must do to Support a Data Culture

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Executives today are faced with many pressing needs. Customer success, your P&L, internal politics, shareholders and investors, managing your teams, strategy and goals, keeping your key projects moving forward. But there’s a new growing factor to add to this never-ending list: Data.

You hear about it from Harvard Business Review. You hear about it from Forbes. You hear about it from McKinsey, and the Wall Street Journal, and CIO. You hear about your competitors doing things with data to get an edge.

In a previous article, we talked about the critical components of making data work in your organization. Hint: It isn’t just investing in a data science team and then waiting for profits to roll in.

Culture change must be part of the equation. Probably not what you wanted to hear, but that’s what it’s going to take. Changing your team’s culture takes several things, but the critical part we’re discussing today is the top-down approach.

Here are the five starting items that executives need to consider when implementing your data culture change.

Support a data-informed decisioning culture

This is first because without this then there simply isn’t anything else. Everyone in your organization must be on board to seek out data, learn from data, and make decisions based off analysis. A core tenant of hiring, promoting, and rewarding people needs to be off of strong data-informed decisioning. This applies just as much to executives themselves as their staff. Too often data is produced to back a gut-based decision and proper analysis and experimentation not performed. Then, when something does not workout then people raise their hands saying the data told them to do so but instead data just supported the desired outcome. There is a component to this item which requires that data and ability to access and analyze it must be put in place and maintained through proper data governance and self-service business intelligence platforms.

Support your Key data champions

Every organization needs data champions to keep your momentum going. You should have many of these data champions, embedded in the business lines, singing the praises of analytics and what data can do for them. Who are your data champions? Are they being recognized, rewarded, and empowered in their efforts? It is vital that executives understand that data champions are needed to drive data culture bottom-up.

Support data-informed decisioning technologies

It is no surprise that having appropriate data and analytics technologies available for not just the analytics teams but also the business teams is a must. Having the proper tools to do the job whether it is Tableau, Qlik, Power BI, Domo and others. That data and ability to access and analyze it must be put in place and maintained through proper data governance and self-service business intelligence platforms.

Support an information-sharing culture

It is not alright for departments to silo off data so they can benefit from it and other departments can’t. Yes, there are instances that data cannot be shared for various data privacy reasons. But, when data is shareable within an organization, the default should be to do it. It is not alright for departments and people to indiscriminately put up data silos against other areas of the company.

Support organization-wide data literacy

Data literacy is essential for all of your employees. This doesn’t mean that everyone needs to be a data scientist. In fact, there are different levels of data literacy needs depending on organizational roles. First, understanding your employees’ data literacy is essential. Then, helping those employees close data literacy gaps with training that is done in an engaging and practical way.

All these items are essential for executives to drive a data culture. However, it is really important to point out that executives must eat their own dog food. No longer is it alright for you to tell others to do what you say, now what you do. Demanding data in your own decisions and even getting hands-on with an executive level dashboard should be expected.

Taking these items and putting into practice will help create a data culture at your organization. Then, everyone will not only be speaking the language of data together and making decisions on analysis in a sustaining data culture.

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

Who is Driving your Data Culture? The Role of the Data Champion

Jordan Morrow - What Data Literacy can do for you

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“You can’t just throw data like spaghetti against the wall and see what sticks. Think about outcomes you want to acheive”
— Jordan Morrow

Jordan Morrow is on a mission to help organizations and individuals become data literate. He believes that the ability to speak, read and write data will be the next big differentiator in the next few years. He travels around the world speaking with people about how to improve their own data literacy.

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Jordan is also just really fun to talk with. We ended up chatting for a long time (we edited it down a bit for your sake) about Data Literacy and how it fits into Data strategy, Data culture, Data science, and how it can drive real, tangible outcomes for organizations.

We also talked about a real-life example of what Data literacy and good Data culture looks like. The Avon Somerset Police Force is enabling their staff and officers with data, helping them understand how to interpret the results and what to do with it, and it’s having a real, positive impact on how they do their jobs!

We asked Jordan how an organization like that could get to a point where they were changing culture. It boils down to three things:

1) It starts with a leader who understood the value of data

2) It requires training. Not just for analysts sitting back at the home office, but for the officers out patrolling the streets each day

3) It requires communication, roll-out and adoption plans to ensure the culture change “sticks”

We talked a lot about an outcome-based model to make data truly powerful. Let’s start with what we want to achieve… “We want more sales”, “We want more return on equity”, “We want higher employee engagement”. Let’s start there and then bring data to the table to help solve that. The worst thing we can do is use data to confirm our own biases.

One of the cool projects that Jordan works on is the Data Literacy Project. As the board chair, he started this project as another way to help people and organizations become more capable with data (Dare we say… Data Able?). It’s a fantastic source of stories and tools to help YOUR organization get started.

We had so much fun talking with Jordan and can’t wait to have more chats in the future!

Thanks so much for coming on the show!

More about Jordan Morrow

Connect with Jordan on LinkedIn: in/JordanMorrow

Check out the Data Literacy Project: TheDataLiteracyProject.org

Follow Jordan on Twitter: @Analytics_Time

Links and References

Book - Can’t Hurt Me: Master Your Mind and Defy the Odds by David Goggins [Explicit]

Book - Freakonomics by Stephen Dubner and Steven Levitt

Podcast - Data Skeptic by Kyle Polich

Podcast - Joe Rogan Podcast [Explicit]

Podcast - Revisionist History by Malcolm Gladwell

Blog - Qlik’s Data Literacy Blog