Gift Ideas for Data and Visualization Lovers: 2016 Edition

The trees have lost their beautiful fall foliage, the days grow shorter and icier, and our pants have gotten tighter from all of the pie that we ate at Thanksgiving. All of this can mean only one thing: it’s officially the holiday season! It may be the most wonderful time of the year, but it can also be the most stressful. There are always those people who are just impossible to shop for, and data viz lovers are no exception. To help with the dilemma, we’ve compiled a collection of what we think data and visualization fans would most like to receive. Grab a mug of steaming hot chocolate and get ready to shop!


I know, I know. Books are on every gift guide, but hear me out. 2016 saw the release of some incredible publications on topics such as daily data visualizations, how to pick the right chart for your data, and becoming a more persuasive speaker, just to name a few. These books are not just informative and interesting, they have also most likely been in your data viz enthusiast’s Amazon cart for some time. So while books may not be the flashiest gift, they're something that the people on your list truly want. Here are some of our favorites:

Better Presentations: A Guide for Scholars, Researchers, and Wonks by Jonathan Schwabish

Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel by Jorge Camões

Data Visualisation: A Handbook for Data-Driven Design by Andy Kirk

Dear Data by Giorgia Lupi and Stefanie Posavec

Effective Data Visualization: The Right Chart for the Right Data by Stephanie D.H. Evergreen

Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations by Scott Berinato

Illuminate: Ignite Change through Speeches, Stories, Ceremonies, and Symbols by Nancy Duarte

The Truthful Art by Alberto Cairo

Data Fluency: Empowering Your Organization with Effective Communication by Zach and Chris Gemignani

Prints & Posters

What could be a better gift for someone that loves data and visualization than an actual data visualization? And with so many options, you can easily match it to other interests and hobbies. Political junkies can enjoy visual histories of the Republican and Democratic parties available over at Timeplots. Your friend that happy-cried when the Cubs won the World Series can remember it forever with Chartball’s visualization of the 2016 season. And for everything else, there’s Popchart Lab. They have an incredible amount of visualizations ranging from a charted cheese wheel on an actual cheese platter, to all the varieties of beer, to a chart about nothing.

Data Products

Wearable technology that provides personalized data and information? Sign us up! Fitbit recently released the Charge 2, which not only tracks daily activity and sleep but also measures how your cardio health compares to people similar to you. An option for someone who may not want an attention-drawing wearable on their wrist is the jewelry from Ringly. Ringly offers rings and bracelets that track similar activities as the Fitbit (such as calories burned, steps, and floors climbed), but also syncs with your phone and sends app notifications. And who says data products are only for people? Let Fido in on the action and check out Nuzzle. Though currently only available for pre-order, Nuzzle is a smart pet collar that ensures that if your pet ever gets lost or sick, you’ll know. It uses GPS and temperature monitoring so that you can check in on your pets from your phone and see how they’re doing throughout the day.


There are two very useful card sets that debuted in 2016 that would both make great gifts. The first is the Data Visualization Chart Chooser Cards, a Kickstarter that quickly gained momentum not long ago. Similar to Juice’s own Chart Chooser, the cards help the user to select which chart is best for displaying and communicating specific data. The other card set that would make a great gift is the pretty and practical set of Graphic Continuum flash cards from Severino and Jonathan Schwabish. 


A few months back, Alberto Cairo demonstrated the importance of visualizing data before putting your blind trust in summary statistics with the Datasaurus. The tweet quickly gained popularity, and thanks to the power of the Internet you can now get the Datasaurus on t-shirts, mugs, pillows, and phone cases. Fashion meets function meets data viz, and something that the data nerd in your life will think is a hoot.

Subscriptions & Donations

Perhaps one of the best gifts you can give the data and visualization lover in your life is a subscription to a news source that routinely produces impeccable graphics and charts. Outlets such as the Washington Post, The New York Times, and The Guardian are all great options for someone looking for timely data visualizations. If the person already has a subscription to one (or all) of these, consider giving the gift that keeps on giving and make a donation in the recipient’s name to ProPublica.

Did we miss your favorite data-themed gift to give? Let us know! Send us a message at Most importantly, have a happy holiday season!

Data Product Resources

The concept and creation of data products isn’t a new phenomenon, but it is something that has started to gain an increasing amount of attention recently. A rising topic within the data industry, more and more organizations across the world are beginning to question what data products are and how to get started building them. There isn’t a ton of literature on the subject, but there are some emerging thought leaders who have been vocal on the subject and who Juice often turns to when looking for inspiration and guidance. If you’re looking for more information on data products, check out some of the people and organizations below.

DJ Patil

Ok, so this one you’re probably already familiar with, but we say it still warrants a mention. If the data world had rockstars, DJ Patil would be right up there with Bono. He’s the U.S. Chief Data Scientist, and, among other accomplishments, created the definition of data products that was part of the inspiration for Juice CEO Zach Gemignani’s presentation at this year’s Nashville Analytics Summit, Data is the Bacon of Business. If you’re looking for information on data products, check out “Everything We Wish We’d Known About Building Data Products”, an article that covers a presentation he gave at First Round’s CTO Summit on the peaks and pitfalls of building data products (or you can follow him on Twitter).

Kevin Smith/Next Wave BI

Every time Kevin Smith of Next Wave BI posts a new blog post on data products, we get a warm, happy feeling inside. Kevin knows his stuff -- he’s been building data products for over a decade, and in that time has gained invaluable insight into what works and what doesn’t. Through his blog and social media accounts, he shares his unique perspective into data products, dashboards, analytics, and so much more. We recommend his post “The Five Biggest Mistakes in Building a Data Product” in particular; it’s a great piece on how the non-technical aspects of data products are likely to trip you up, and how to circumvent them.

Blue Hill Research

A research and advisory firm that focuses on enterprise technology, Blue Hill has become one of our go-to places for interesting articles on data products. They also cover subjects such as dashboards, big data, and analytics, and mix a unique view with a fresh voice. We’re partial to the post “Data’s New Role in the Enterprise: Build Data Products. Make Money”, but we admit we may be a bit biased. Check out their blog for more content on data products and data monetization.

Juice Analytics

It was the great Leslie Knope who once said, “I am big enough to admit that I am often inspired by myself.” While we may not go so far as to say we inspire ourselves, if you’re looking for more information on data products take a look at our entire collection of blog posts on the subject (and check back often, as we are constantly adding to it!).

Of course, these are just a few starting places to learn more about data products. If we missed your favorite data product resource, let us know at or send us a message.

Three Keys to Data Monetization Success

“You may have heard in your organization that [data monetization] should be easy -- repackage data, find customers, sell product, achieve success -- mission accomplished,” writes Lydia Jones, InSage founder, and Karl Urich, president of DataFoxtrot, in a recent article on Tech Target. But while the process of monetizing your data may seem straight-forward, it's actually much more complicated and nuanced than it first appears and it requires a plan. 

Like with most new projects, the hardest part for an organization looking to monetize its data is getting started. With so much involved in the process, it can be overwhelming to know what to take into consideration when creating a data monetization plan. Jones and Urich shared three things organizations should evaluate as they begin the process of data monetization and we think they gave some great advice.

Evaluate business opportunities

One of the first places to start to build your strategy is to have a solid understanding of the types of businesses and industries that can benefit from your data. Sounds simple, right? Jones and Urich go on to explain that it takes more than just looking around at the organizations in a similar industry - you should also take into consideration those that aren’t as obvious.

Jones and Urich give tips on how to identify those industries, and we’d add that one of the easiest ways to identify the kinds of organizations that can benefit from your data is to ask this question: What pain point can my data solve? Once you can answer that, it makes it much easier to identify potential customers. It also begins to give you direction. Knowing the problem you want to solve for customers is a key starting point for building a successful product. 

Evaluate data regulations

There’s nothing worse than investing a substantial amount of money, time, and energy into your data monetization plans, only to find that they’re not viable due to data regulations. “In the United States, data privacy is regulated on a sector by sector basis,” Jones and Urich advise. You should be familiar with the regulations in all potential customers’ industries.

Evaluate cost/benefit

Evaluating the cost and benefit of monetizing your data starts with two questions: “What will it cost to build and maintain over time?" and "What price will people accept?” This may take some time to fully understand, but it's an important question.

Keep in mind as you consider what price and pricing models you should adopt, that it’s not just about the data being sold, but about the insights, metrics, etc., that are a part of your data. Don’t simply position your information as raw data, but as but rather as a solution that solves a problem.

These three key points are an excellent starting place for your journey to monetize data. If you still have questions about getting started or about data monetization and data products in general, check out some of our blog posts on the subject or send us a message.

A Blueprint to Insight

It's often easy for me to take for granted the insights I regularly receive from data. Whether that be from tracking a run with my Fitbit, looking at likes and views on social media, or using Google Maps to help me avoid traffic. Working for a company that has the word "Analytics” in its name means that I spend a lot of time in data, and working for a company as creative as Juice means I get the opportunity to truly enjoy navigating data as a visual experience.

I have mentioned our new product Blueprint a couple of times already, but I wanted to share some of the insights we've been finding in hospital and health system data and how that data affects internal decisions. According to a study from Becker’s Hospital Review, a hospital's workforce accounts for 54.2% of a hospital's overall operating costs. These people are a huge investment, and so the hospital needs to make sure that it's hiring and retaining the best people. It can be quite the undertaking to make sure that the Emergency Department has staff with enough experience to adequately do the job, or that hospital supervisors are retaining top talent.

As we have been digging into some of these different facilities' workforce data, we have started to come across varying insights that have turned out to be valuable to hospital leadership. For instance, Blueprint can show a Chief Operating Officer where she has the opportunity to consolidate. There are often multiple people who are spread out across a facility which could be consolidated into one or two units, reducing overhead. For a larger hospital system with multiple facilities, Blueprint can allow a leader to compare facilities across their enterprise. With this information they are able to compare by important metrics and ratios like staff-to-supervisor ratio, or staff to provider ratio across all their facilities.

Turnover, often a primary concern for HR, is another hot spot with which Blueprint helps provide insight. Recently, Blueprint was able to help a pilot customer that manages over 40 senior living communities locate the departments and managers with the most turnover. As we have continued to discuss Blueprint with HR leaders, they have expressed the need to be able to tie turnover to root causes like compensation or employee engagement. Since Blueprint is designed to take a large number of staff and find further subsets, it can act as a funnel to get you to the group of people you are looking to take action on. I was talking to an HR Director at a hospital yesterday who was saying that she has a hard time tracking the number of interns they have at any given time and what departments they are in. Using Blueprint, we were able to find that information within a matter of a couple of clicks.

By taking the HRIS data of a hospital and health system and categorizing it in a meaningful way, we feel as if we have stumbled onto something truly valuable. The finish line being helping hospitals and health systems build a successful Blueprint for their organization.

Want to know more about Blueprint and how it could help your organization? Drop us an email. We'd love to hear from you.



Driving Healthcare Data Culture Forward

Last week, Juice Analytics participated in the Health 2.0 Atlanta panel, a co-hosted event by the Data Science and BI Society of Atlanta and Health 2.0 Atlanta. The focus was on analytics and healthcare and it was a great event. There was so much interest, they had to move the event to a larger venue! That tells me two things - (1) people want to get more out of their data and (2) Healthcare is behind and they really want to catch up. Two of my favorite “tweetables” of the night, said by Jason Williams, VP of Analytics and Strategy at McKesson, backed up those assumptions.

Getting more out of your data

The first “tweetable”  was something we see at Juice all the time: “Nobody wants analytics, people want answers.” This relates back to people wanting more out of their data. Right now many people simply have data - and that’s it. But people want more than just a bunch of charts and numbers on a screen, they want insight. They want to be told where the problem is and given insight into how to fix it. If you’re simply delivering data either in a spreadsheet or just a series of charts, you’ve missed the mark. And for the record, this problem isn’t specific to healthcare. It’s all over.

Catching up in Healthcare and the path forward

My other favorite “tweetable”, originally said by W. Edwards Deming, was “In God we trust; all others bring data.” To get buy-in on a problem and solution, you need the data to support your position. The problem is that not everyone is ready to embrace data. As the quote alludes to, it’s all fine and well to think or believe you know the answer, but data helps you actually know the answer. Sure there can be a human element involved, but being informed with data to back up decisions is useful and important. In order to move data in healthcare forward, there needs to be a culture around data. It needs to be ingrained in an organization as useful and be included in everyday conversation.  

Embracing a data culture in healthcare will become even more important as we move into the future of what healthcare could look like. Much like Google Maps on your phone adjusts your course based on a wrong turn or an accident on the highway, it was said that healthcare will begin to use data in much the same way. Healthcare data should and will move in the direction of being event driven and using data to adjust as things are happening, rather than being reactionary. I don’t know about you, but that sounds exciting and full of promise! But to get there, you first need a good data culture.

The event was not only a great success, it was insightful - which is what we love! It would seem that to begin to move your healthcare organization forward, there are two things to focus on. One would be providing insight, not just data. The other is to promote a culture of data that is widely adopted within the organization. Without that, having insight won’t matter since nobody will want to use it.

To learn more about creating a data culture in your organization, check out Data Fluency: Empowering Your Organization with Effective Data Communication, written by Juice Analytics founders Zach and Chris Gemignani.

To learn more about how we help our healthcare clients provide data insights and succeed, check out our case studies or get in touch.


How to Build Better Data Products, Part 2: Development

This is the second in a multi-part series on launching successful data products. At Juice, we’ve helped our clients launch dozens of data products that generate new revenue streams, differentiate their solutions in the market, and build stronger customer relationships. Along the way, we’ve learned a lot about what works and doesn’t. In this series I’ll take you through what you need to know to design, build, launch, sell, and support a data product. Read Part 1 of the series here.

If “Data is the Bacon of Business” (TM), then customer reporting is the Wendy’s Baconator. Sure it contains bacon, but nobody is particularly happy with themselves after eating it.

In a recent blog post, we described the differences between customer reporting and data products. Those differences result in some very different functionality requirements. In particular, data products require more C.L.I.C. D.R.A.G.

  • Context — Benchmarks, comparisons, trends, and/or goals that encourage decision making.
  • Learn — Help and support features to train users to get value from the information.
  • Integration — Connections with other software systems to integrate with data and enable operational actions.
  • Collaboration — The ability to save insights and communicate them with other people. Decisions aren’t made on an island.
  • Documentation — Because data products live on and touch many people within your organization.
  • Reporting — To track usage of the data product.
  • Administration — Features to manage users and control permissions.
  • Guidance — To point users to the most effective ways to explore and understand the data.

This collection of capabilities gives some indication of the gap between your standard customer-facing reporting and a complete data product. To accomplish all of these, you’ll need more than a talented BI report writer and access to your database. In our experience, the recipe for building a successful data product is dependent on a number of specialized roles.

Product Manager

The Product Manager sets the vision of the product. He gathers the necessary resources to make the team successful, and builds organizational support for the product.


UI/UX Designer

The UI/UX Designer understands the user’s workflow and how to best guide the user to decisions. She crafts the interface and interactions to make the data intuitive. She's also in charge of design application styling and all visual elements.

Business Analyst

The Business Analyst translates application design into technical and data requirements. She's responsible for documenting business logic as product decisions are made.


Front-end Application Developer

The Front-end Application Developer's role is all about building interface elements, interactions, and data visualizations.

Back-end Application Developer

Data Guru

The Back-end Application Developer does everything the Front-end Developer does, only backwards. Just kidding! But he does build the application server environment an define data queries to support UI interactions.

Data Scientist

In addition to having the coolest title, he provides access to raw data sources. He understands and communicates the meaning of data fields and calculations to the development team.

Technical Architect

The Data Scientist defines the questions that will help end-users make better decisions. She enhances data through predictive modeling and other advanced data analytics techniques.

Quality Assurance Engineer

He's the general technical architecture of the product, responsible for figuring out how the application connects to data sources and integrates into other systems.

The Quality Assurance Engineer evaluates whether the data product meets the need and requirements set out in the design process. He also tests data accuracy and product functionality.

It's a big load. That’s why you might want some help before going at it alone. At Juice, we've built a technology solution and an expert team that fills out many of these requirements. We have a set of visualization components and interactive features that ensures your application is a first-class user experience. Combined with our experienced design and implementation teams, we’ve got many of the resources covered. Our clients bring the product vision; we make it happen.

Our goal at Juice is to streamline the data product launch process so you can launch innovative data products in weeks, not months. Want to know more? Let us give you a demo.

Communicating Economic Progress with Visual Analytics

Earlier this year, we worked with The Virginia Chamber of Commerce to help bring their vision for a new data application focusing on economic performance in Virginia to life. They wanted something that would fit within their overall website and serve reliable, timely data that’s easy for everyone to use and easy to share. With insights around performance, transportation and trade, innovation and entrepreneurship and more, their new application allows everyone to find useful and actionable insights within the data. A couple weeks ago, we had a chance to speak with Barry Duval, President and CEO of the Virginia Chamber of Commerce, to get his insight on the project, how it went and what the feedback has been so far. 

1. Tell us a little about the Virginia Chamber’s mission and how you communicate with constituents.

Put simply, we advocate and we communicate. We are the voice of Virginia business. The Virginia Chamber is the largest business association in the Commonwealth, with more than 25,000 members. Our mission is to be the leading non-partisan business advocacy organization that works in the legislative, regulatory, civic and judicial arenas at the state and federal level to be a force for long-term economic growth in the Commonwealth. We communicate with public policy makers, members of the media, and the general public through personal relationships developed over years, traditional earned media, social media, paid media, and widely attended events focused on issues of importance to the business community.

2. What was the problem you were trying to address when you set out to create this application?

Whenever you are advocating for a policy change or demonstrating a problem that needs to be addressed, you need to have trustworthy data to support your position. There are many metrics to measure Virginia’s progress in various policy areas that contribute to economic growth, but public policy makers and business leaders alike have asked us for a single place they can go for reliable, timely data that’s easy to digest and compare with other states and between jurisdictions in Virginia.

3. What were you doing previously to solve that problem? What parts of that approach were not working?

We give presentations around Virginia that visualize certain important economic metrics, and often have requests to receive the PowerPoint presentation for future use and adaptation to a group’s or individual’s needs. We communicate issues such as Virginia’s recent drops in national business and legal climate rankings through op eds, press releases, and traditional media interviews. However, none of those efforts give interested individuals easy access to use the data that our staff is able to compile for their own purposes

4. What appealed to you about working with Juice and Juicebox as a solution?

We saw the work that Juice and Juicebox did for the US Chamber of Commerce on their dashboard, and use it as a frequent resource in the course of our work. They came highly recommended for their responsiveness and expertise in this this area. We wanted to work with a company who not only had the visual and graphic design expertise to create our dashboard, but also the economic understanding to understand how to present complex data in a way that’s easily understandable and simple to navigate.

5. What kind of feedback have you gotten on the application so far and from whom? How has it impacted your conversations with members and stakeholders?

We have not yet launched the dashboard, but when presenting screenshots of the application to executives from other chambers of commerce in Virginia and to the members of our board of directors, the response has been overwhelmingly positive. Local and regional chambers have been particularly interested in the ability to compare certain metrics at the regional level. We anticipate a public rollout and demonstration December 2nd at our annual economic summit in Williamsburg.

6. How do you feel this application represents the Virginia Chamber compared to the sites that other chambers have?

We launched a new website last winter to make it easier for our members to access Chamber resources and to reflect a more contemporary feel. The application produced by Juice fits hand in glove with the goal of our website to be useful, intuitive, and attractive for members, potential future members, and for public policy makers to find valuable, trusted information.

7. Have you learned anything interesting through exploring the new application?

The feedback from Juice as we have gone through this process has led us to rethink the way we use some of our data and led us to include new metrics that we otherwise may have overlooked. It has not been simply a process of beautifying the data we were using, but has given us new insight into how we measure progress in the Virginia economy, which benefits our members and adds value to all of the other communication outreach that we do as a Chamber. 


To learn more about data products and visual analytics solutions, get in touch! We'd love to chat!

10 Differences between Customer Reporting and Data Products

We’ve been talking a lot about how innovative companies are realizing the need to enhance their solutions with more customer-facing data products. For example, GoToMeeting launched a new feature called “Insights” where they send you engagement summary information from your meetings. Here is one from a recent Juice Lunch & Learn:

DJ Patil (U.S. Chief Data Scientist) defines data products as "a product that facilitates an end goal through the use of data.” I’ve described data products as turning analytics inside-out to deliver value to your customers. But the question we most often get is: How are data products different from the customer reporting we already provide? 

Here are ten important differences between customer reporting and data products: 

1. Instead of summarizing data, solve a problem. Most reporting simply regurgitates data in a semi-aggregated format. A data product starts with customer’s pain points and asks how data can bring insight and better decisions.

2. Instead of starting from the data, start from the customer. Report writers will often look at the data available to them and ask "How can we deliver all this information?" That’s what gets you to self-service analytics tools sitting on top of data. Not good. Data products need to start by asking how you can make your customers smarter and more effective in their job.

3. Instead of stopping at showing the data, guide users to specific actions. Customer reporting may be satisfied with making data accessible. Data products need to do more — they need to move people to take action. Start from the end point: what kinds of things do you want your users to do? How will you give them the right information?

4. Instead of focusing on metric values, deliver context for decisions. Key metrics are only as good as the context you put around them. Data products wrap context around metrics with goals, benchmarks, comparison, and trends. Then your users will know how they should react to the numbers they are seeing.

5. Instead of passive objectivity, bake-in best practices, predictive models, and/or recommendations. “Let the data speak for itself” — that’s like a chef saying: let the diners enjoy the raw ingredients. Bring your expertise to the data product. Your customer knows their pain — but you know the data and what can be done with it.

6. Instead of trying to show more data, reduced to only the data needed. When it comes to presenting information, more data is seldom better. Customer reporting only expands — into dozens of dashboards or reports. Data products should strive for less.

7. Instead of putting the burden on users to figure it out, strive to reduce burden. Customer reporting tosses responsibility to the customer, effectively saying "you figure out what’s important to you.” Data products recognize that few people inherently enjoy messing with data; most people just want to be better at what they do. The data can facilitate that goal.

8. Instead of being designed for analysts, data products are designed for decision makers. Many customer reporting solutions assume the end-user wants to dig in and analyze the data. Data products are for a different audience: front-line decision-makers. These people are busy with their regular job and have little interest in learning something new.

9. Instead of “show me the data”, strive to make the data invisible. The best data products of the future will make the data invisible. Consider how Google Search tries to predict your need and point you to the best answer at the top of your search results. Google wants to hide the data (search results) and jump straight to the answer.

10. Instead of a cost-center for your business, become a profit center and differentiator. Customer reporting is considered a necessary evil for many companies. For example, we’ve had dozens of conversations with advertising agencies who feel compelled to provide reporting, but clearly don’t relish the task. In contrast, companies that view their customer data as an asset recognize that they can create new revenue streams.

That’s where Juicebox comes in — it is the quickest, best path to turn your data into differentiated, revenue-generating data products.

More Analytics Isn’t Always Better

LogiAnalytics sells a self-service business intelligence solution, and they’d probably like to see Fitbit using it. Their sales pitch comes in the form of a blog post ("Why Fitbit Product Managers should be focused on Analytics") critiquing Fitbit for not giving its users a more full-featured, self-service analytics dashboard as part of the fitness product.

The post starts by lauding Fitbit as an innovator, but quickly pivots to suggest Fitbit hasn’t “kept pace” in the realm of self-service data capabilities. Fitbit’s simple dashboard "may have been acceptable some years ago but not anymore."

The evidence: someone pulled data out of Fitbit and visualized it in a different dashboard tool. Never mind that the someone is a demonstration project by another dashboard tool. The LogiAnalytics author concludes that this is proof that "Fitbit doesn’t meet user needs anymore and provides a workaround for customers to export data to another platform for improved self-service analysis.” The post goes on to paint a doomsday scenario for Fitbit: "Instead of instantiating itself into the daily lives of users, it is separating itself out and losing the user by becoming a device that measures steps (and other things)."

It’s quite a leap based on some questionable assumptions. My guess is that more self-service BI in a consumer device probably isn’t what Fitbit product managers should be concerned with. Here’s an alternative set of lessons for companies looking to integrate analytics into their products: 

  1. The plural of anecdote isn’t data. When you find one example of an analysis approach by your customers, don’t feel compelled to add it to your next product release. A better approach: find out what is the pain that is motivating the customer, then talk to other customers to see whether that pain is common.
  2. Know your user segments. I’d love to hear from Fitbit about how they’ve thought about user segments and meeting analytical needs. Given their success, I expect they’ve done their research. At Juice we recently segmented our Juicebox app users into five analytical user segments: Explorers, Light Explorers, Number Checkers, Table Downloaders, and Freshman.
  3. Apps, not busy dashboards. Fitbit has clearly emphasized their mobile app as the primary mechanism for interacting with fitness data. The app interface shows how they’ve thought about making data useful. The data is delivered in service to different user needs: weight loss, competition with friends, step activity, sleep tracking. I wrote about the post-dashboard world here.
  4. Don’t make consumers feel like they are at work. The idea of baking a self-service BI solution into Fitbit feels like a mismatch in expectations. As a consumer, I want simple, easy, fun, and direct. I wouldn't use those words for any self-service business intelligence solutions, regardless of how important they might be in a particular business context.
  5. Hackers want hacking tools. Fitbit created a well-documented API that gives technically-savvy users the ability to pull their data out, combine it with other data sources, and present it any way they like. That’s the ultimate flexibility — not a dashboard with extra nobs or trend lines.

To be fair, Logi offers some legitimate points:

  • "Through our extensive work in BI and analytics, Logi has found that when users get access to data, over time they begin to want access to more data and want to be able to do more with it."
  • "...for smart companies that seek to keep an ongoing relationship with the user know the philosophy of 'don’t lose the user' is critical to maintaining hardware revenue..."

To give LogiAnalytics some credit, they do point out that once users get access to data, the users will always ask more and better questions. Another important message: analytics on top of a device is a good way to enhance and solidify customer relationships. But choosing the right way to deliver that data is the challenge, one that Fitbit seems to have taken head-on.

Finding Insights on Turnover in HR Data

Turnover is a major problem in healthcare, and the costs associated with re-hiring and training new staff can be in the tens of thousands of dollars per person, depending on the position. Turnover costs hospitals and hospital systems millions of dollars each year. Usually each hospital or group of hospitals has an idea what their turnover percentage is, but they may not be drilling into the data to find insights into why turnover is occurring.

We found some commonalities in the reasons for this lack of connecting the dots in regards to turnover. First, there are often multiple dashboards with conflicting information. This causes problems across an organization as managers are working from conflicting numbers. Second, the data is living in different places and this costs time and money as leaders have to go to multiple sources to get their information. Lastly is the lack of ability to tie the turnover back to specific departments and supervisors with certainty.

What we discovered is that many HR professionals in healthcare are looking to their HRIS systems to provide answers to their turnover problems. The problem is that these systems are not designed with that purpose in mind. They are a place to store data and access pieces of it when needed, but they are not designed to connect the dots between the different pieces in the system.

In a recent conversation with the Chief Human Resources Officer (CHRO) of a health system, I was struck by the way he took responsibility for the turnover issues he was facing in his facilities. Turnover is something personal for him - he looks at his 4,500 employees as his direct responsibility, and as such takes it upon himself to ensure that he is hiring and retaining a workforce that knows they are valued.

My CHRO friend is one of the first in his field to take the data in their HRIS system and work to do something creative with it. They have been piloting Juice’s new product, Blueprint, for the last 10 weeks and have begun to find a correlation between turnover and supervisors in their organization. He told us that he has never before had the ability to, in one place, find turnover per supervisor and per department in such an accessible manner.

Blueprint is built like a funnel: you choose a metric at the top level that summarizes some information across all of your staff allowing for an enterprise view of that metric. You are then able to follow a path as you drill down to an actionable list. For instance this CHRO was interested in understanding why a certain subset of his 4,500 staff members have remained there for longer than 10 years. He was able to turn a list of 4,500 staff into a list of 40. Previously he would have needed to go through two or three layers to get this data, and now he can find it in a matter of minutes. Now he has the information he needs to figure out what causes employee turnover in his organization and can take actionable steps to decrease turnover in the future.

As this organization works to get a handle on their turnover problem, Blueprint has proven to be an invaluable asset. It has allowed the organization to quickly and efficiently find the necessary data and take action on it. If you're interested in learning more about Blueprint, send us an email at or set up some time to talk-one-on-one.