What is this self-service BI thing?

What is this self-service BI thing?

Episode 001

What in the world is Self-service BI and why should anyone care about it? Is it just for analyst-types?

What in the world is Self-service BI and why should anyone care about it? Is it just for analyst-types?

One of our favorite topics to kick off this podcast! Matt has been building self-service analytics initiatives in Fortune 500 companies for 7 years now, so he’s excited to talk about it with you!

The foundation of self-service analytics is in allowing non-technical users throughout an organization to access and use data to identify insights, communicate results, and drive decision making.

Why would an organization choose to go this route? What are all those analysts getting paid to do, anyways? Well, in the age of information, there’s far more data than any single analyst team will be able to mine, process, and communicate. You want your technical people working on the really challenging problems like sourcing new data, cleaning data, and more advanced statistics & machine learning.

What this does is it frees up the business to move at THEIR speed. If they need an answer now, then you’ve given them the tools to get that answer, rather than being put in a queue. You want the data as close to the decision-making as possible, and as fast as you can. Democratizing the data can help you make that happen.

Make sure to subscribe to more episodes with your favorite podcast catcher!

Thanks and Happy Listening!


 
 

Name it and they will come

Name it and they will come

Episode 000

We are on a mission to help high-performing individuals become champions for a more data-driven approach in their organizations

We are on a mission to help high-performing individuals become champions for a more data-driven approach in their organizations

Welcome to the Data Able Podcast!

Dave Mathias and Matt Jesser are proud to bring you a brand new podcast all about data. our goal is to help people like you to champion data in your organization and truly transform yourself into a data-informed culture.

How are we going to do this?

We think podcasts are a great way to provide high-quality information in a tight and compact way. So we’re going to be delivering weekly, quick-hit episodes on topics that your organization needs to be thinking about. These 10-minute episodes are easy listens, and will arm you with ideas and talking-points that you can use to drive the data-culture in your organization.

We’ll also deliver longer-form interviews with amazing people with a similar passion for data, who are doing work just like you… helping change your organization with data.

Our first (zero-eth?) episode is a light-hearted look at how we came up with the name for our podcast, and what we’re looking to achieve.

We look forward to starting this podcasting journey with you! Until next week!

Thanks and Happy Listening!


 
 

Why it's critical that leaders become data literate

Nearly every organization is undergoing a digital transformation and as part of this data literacy or data fluency plays a pivotal role. Data like any language is effective when others around you understand it and make decisions based on its meaning. But, data fluent doesn't mean being a data scientist. Instead it means "the ability to understand and use data effectively to inform decisions" according to Mandinach and Gummer. [1] One addition to this definition would be ability to communicate with data.

Leaders with data fluency whether team leaders, department directors, or senior executives benefit. These data fluent leaders ask questions like those below but more importantly are able to make data informed decisions.

  • What are key metrics that help me understand my customer's experience?

  • Am I hiring, rewarding, promoting and training my team members to be data fluent?

  • What data can I share with others to empower them to make the organization better?

  • Am I being a good data steward and ensuring proper data privacy and ethics are being utilized?

  • How can I use data to make our operations more efficient and effective?

  • Am I communicating with data appropriately to show the value our organization

  • What new data could I seek out or capture to bring more organizational value?

  • What percentage of employees have access to self service business intelligence and analytics and have been trained on it?

  • What metrics do we track to measure our employee experience?

  • What percentage of data we capture are we using to inform decisions?

  • I understand my NPS is in the top quartile, but what is driving this metric and what other metrics should I be monitoring to understand my customer satisfaction?

  • How are we developing new products and services based upon data from our customers?

Data fluent leaders are able to help their organizations have a data driven or data informed culture. Doing so will not only lead to more fulfilling environment and to great success.

Are you a leader interested in helping your organization be data fluent? Reach out and let’s discuss if we can help.

 

[1] McAuley, D., Rahemtulla, H., Goulding, J., & Souch, C. (2014). How Open Data, data literacy and Linked Data will revolutionise higher education. Retrieved from: http://pearsonblueskies.com/ 2011/how-open-data-data-literacy-and-linked-data-will-revolutionise-higher-education/



 
 

How business and tech partners can better work together

The Twin Cities Data Fluency Group had its second meeting in May. This month involved an engaging discussion on “How the business can better work with analytics and tech partners.” Tricia Duncan and myself (Dave Mathias) moderated three great panelists – Nate Hallquist from Syngenta, Serena Roberts from Capella, and Jack Vishneski from ThreeBridge and consulting with Cargill.

There was a lively discussion on several fronts, but key takeaways were as follows:

  • Building relationships is key. Most information work takes teams and that means working with people. The more you build relationships the better chance to succeed as Nate mentioned.

  • Bring everything back to problem being solved. Data and analytics only serve a purpose if they solve problems. As Jack succinctly mentioned it is all about solving problems and bringing conversations back to those problems will help ensure success.

  • Trust is key. As Serena mentioned being a trusted advisor as an analyst and business partner alike is a must. Serena has the unique experience playing both roles in sales and sales enablement and building trust with both these hats has been essential to her success.

  • Rapid prototyping should be norm. Rapid prototyping is a must for dashboards and both to help ensure customer satisfaction and efficiency. These rapid prototypes can be done in a dashboard tool if a similar dataset available but just as nice it can be hand drawn on a whiteboard or paper.

In addition to these takeaways, there was a good discussion on the role of self-service business intelligence (BI) and how much autonomy the business should have and how much of it stays in the analyst, data science, or technology hands. There was mixed feeling here both on panel and in audience. Some companies have shown more success than others in distributing data fluency and technology into the business. However, there was agreement that tools are making it more able for end users to do more challenging problems.

One metaphor that seemed to resonate is treating self-service BI as a grocery store and not a treasure chest can help. As Nate described this the analyst, technology, or data science groups ensure that often used data has been made available with appropriate cleaning, integrity, and trust to business users. However, organizations need to ensure end users have proper training, tools, and help available so they can focus on conversations and insights while reducing the risk of invalid data models or technical debt.

There was a lot of overall agreement that data fluency is critical for organizations broadly and the language of data will be more easily picked up by some than others. But, to have a data-driven or data-informed culture at an organization requires your people to be data fluent.

This is a short summary of the great discussion that occurred, and all are welcome to attend the next TC Data Fluency MeetUp will be in July (date TBD). If you are an analyst or data scientist, then this is a great opportunity to bring one or more of your business partners to help further your relationship.

Thank you to Nate, Serena, Jack, and everyone that attended, and Tricia, Nate, and I hope to see you in July.



She Talks Data Perspective From a He

Earlier this month I had the opportunity to attend the She Talks Data MeetUp in the Twin Cities. This group’s goal is “[o]ur goal is to build a close-knit community of women (and men in support of women) who can come together to grow professionally and personally.” It was started as an offshoot of the She Talks Data group in Silicon Valley a few months ago locally by Serena Roberts and Laura Madsen.

Serena has said several times that this is not just for women. Plus, one of my friends, Karla Hillier, was presenting, so I thought great to support her and at same time attend this new group and learn.

As I told Serena beforehand, I was afraid attending and how I would be received and feel. But my fear quickly dissipated from the moment I walked in. Right from the start it was an engaging and welcoming environment, but I did feel something different.

As the first speaker Emma Denny, an employment law attorney, kicked off right from the start the room was riveted. There were questions related to workplace discrimination and sexual harassment. Emma talked about rights that people had in Minnesota. But, she also talked about the high thresholds that people face in these cases and difficulty in proving these cases. There were great tips such as telling people in writing when they felt harassed and literally spelling it out that you think it is because of gender or other protected class.

At one point, Emma asked how many people in the room had felt discriminated or harassed at work and nearly everyone’s hand was raised. I can say I felt bummed and really more angry. I felt angry that so many talented amazing people in our community have felt discrimination and harassment. I felt angry that so many of amazing people will likely face this more as their career continues. I felt angry that people often time creating those environments are oblivious that it is even occurring until it is too late or worse don’t care.

After the group I reflected what I could do. Yes, as a product person at heart my nature is when I see a problem I want to help find a solution. Of course, there is no single solution, but we can all help one action at a time whether in groups or at work to provide a more inclusive environment.

I encourage other men to respectfully participate in She Talks Data and other groups like these where appropriate and where welcomed. Not only as a sign of support, but also to be in a better position ourselves to be supportive when challenging situations with bosses, colleagues, employees, and clients will inevitably occur. After all we are people on this journey of life together with a finite amount of time, so let’s make the most of it and support each other through it.

Shout out to all the great people I met and good conversations I had. Special shout out to: Jen Roberts and Tricia Duncan that I had pleasure of meeting and sitting with; Serena Roberts and Laura Madsen for organizing group locally and continued leadership in community; and Emma Denny and Karla Hillier for sharing their knowledge and inspiring others.

Interested in learning more? Go to the April 4th She Talk Data MeetUp and catch April Seifert who will be one of the presenters. In fact, April and I were just talking this morning on all things CX, analytics, and podcasting and sure she will have a lot of great wisdom to share.