A Recipe for Success Metrics

When you’re getting out that last minute proposal or responding to the 4:55pm ad-hoc report request, metric performance is not top of mind. As a result, thinking about success metrics, in light of all our other demands, can make us feel less than successful. Knowing that you need to implement or improve your success metrics can feel like a daunting task with all that is going on around you.

Having successful metrics is very similar to getting really good at a family recipe. It's not a one and done, but an iterative process that is made up of a series of small steps and adjustments (pivots) over time. I’m sure it sounds odd, but here are some things that metrics have in common with a great family recipe:

• Outcomes vs. Metrics - It's about creating a great conversation and experience, not collecting and publishing numbers. A successful Thanksgiving recipe is the family discussion and memories that go on for years, not the knowledge of how many sticks of butter were used. 
• Mistakes Happen - There’s always a Metrics or Report 2.0 (3.0 and 4.0 too), so recognize it's a process that will only improve over time.  
• Context Matters - A one pot recipe to throw together after Tuesday night soccer practice is different than something for Christmas Eve dinner.  The same can be said about the daily update vs. an annual report.  Ultimately, the desired outcome is different, so even if the metric is the same; how its shared and communicated might be different.  Remember it's about “success metrics” not just metrics, so having success is an important part of the equation.

With Juice’s 10+ years of building metric dashboards and data products, the topic of success metrics comes up often. Getting started with metrics is similar to getting that family recipe just right. It will take time, but is worth the effort. As a follow up to our 2006 blog post on success metrics, and a recent post, Goals and Metrics like Chocolate and Peanut Butter, here’s our recipe for successful success metrics:

The Recipe for Successful Success Metrics

Follow a Recipe

When getting started or having limited time, use a recipe. Minimize risks and give yourself the greatest chance of success. People will use your metrics 1.0, so give yourself the best chance of success. Use someone’s else’s metrics (recipe) to benefit from their mistakes, etc. It may not be the best fit for your organization, but work through the process of collecting, transforming and aggregating the data, which will be challenging in its own right. As time goes on you’ll improvise, be more creative and generate your own version of the recipe.

Once you have mastered a technique, you hardly need look at a recipe again
and can take off on your own. Julia Child

Use a mix

In metrics 1.0, it's not cheating to use the pre-packaged metrics that you get bundled with your transaction system or anything you get for free. While using vanity metrics is a big no-no, using the pre-packaged metrics (think cake mix), will teach you about the effort involved and the nature of the conversations your audience wants to have. In future iterations you’ll refine your metrics, the calculations, etc. to get them to where you want, but at the outset create something you can easily share with others.   

Fewer Ingredients 

In the spirit of getting something done and sharing your masterpiece, start with something simple. Just like a simple recipe has fewer ingredients, start with fewer metrics. Sure there’s a lot of information, but start with three or four. Use composite metrics (see below) if needed. You’ll certainly have a few dimensions (categories), like date, type, etc., so think 8-10 columns at most. Fewer ingredients (metrics) gives you a chance to be successful and probably more likely to get feedback.

See the two examples below to give you a comparison. It's really hard to have a fruitful conversation about the 1st one with all that information. Start with a few numbers and grow into more complex recipes.

Crowded Dashboard (not a 1.0 recipe)

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https://vimeo.com/47945498

What a 1.0 set of metrics might look like.

Use your hands

One of the biggest challenges we run into at Juice is that people aren’t as familiar with their data as they should be. They’re not sure where the data comes from, how the calculation works or what they hope to accomplish with all their metrics. Well before you buy the  KitchenAid Pro Line get in there and use your hands. See how the ingredients mix, get a feel for the texture, etc. You’ll need this experience to explain what you’ve prepared, but also to address proposed changes for your 2.0 metrics.

It's so beautifully arranged that you know someone's fingers
have been all over it. Julia Child

Pinch of Experience

Having access to an expert, like Avinash in the web analytics space, is great to offer ideas on metrics as well as learn from their experience, much like a chef. Find your industry expert and leverage their content. In addition to our posts on metrics, I like this post a lot about getting started with metrics.

Combine Ingredients (Composite metric)

As I mentioned earlier, sometimes you might need a composite or calculated metric. Don’t start with QBR, save that level of complexity for later. A starting point might be a metric involving simple arithmetic from two columns like Calls per Day or Proposals per Week. Consider these calculated metrics if they’re easy and will improve conversations with your audience.   

Conversation

Ultimately, success is dictated not by your metrics or the beauty of your dashboard (meal), but the conversation that arises from it. My own memories of successful family recipes are filled with thoughtful discussions, sage advice from my elders and anticipation of the next family gathering. Focus your beginning metrics efforts on similar outcomes. Make sure your audience shares this goal as well.

Ready for Metrics 2.0?  Check out Zach’s post from a few months ago, Goals and Metrics like Chocolate and Peanut Butter. Need even more? Head over to the Juice resource page to check out the free content there for more insight on designing information experiences and getting your charts and everything else just right.

The Future of Dashboards

The Dashboard is dead, long live the Dashboard!

At Juice, we’ve long been dissatisfied with the common form of the information dashboard. When it comes to communicating data, I know we can do better than a densely packed grid with 4, 6, 9, or more charts. Why should we ask people to look at a page where each chart is desperately fighting for attention, like the College GameDay signs behind Desmond Howard and Chris Fowler?

#3 in best GameDay signs of 2015

Nevertheless, the conventional conception of a dashboard has been resistant to change due to a couple underlying assumptions:

1. All the information should be visible at once so readers will be able to draw important connections across the data;
2. The dashboard should perform just as well in a static environment (i.e. a print out) as on a computer screen.

Google Image search on “dashboard”. A series of packed grids, always with four or more charts.

Dashboards don’t need to look like this. We can stop saddling users with densely-packed visuals that do little to guide them through the data to insights. It isn't just about using smarter, cleaner, Tufte-compliant visualizations; it is about defining a new concept of what a dashboard should be. I'll call it the Undashboard.

The Undashboard is aligned with the opportunities created by modern interfaces, interactions, and devices. The Undashboard is focused on a data consumer that is tech-savvy, but doesn’t live inside a spreadsheet day-in and day-out. These data consumers are mobile information-workers who want tools to make them better at their job. They don’t have the time or inclination to spend their morning squinting at a complex print-out of tiny sparklines. Data consumers expect information relevant to their job and a user experience that is closer to a mobile app than Lotus Notes.

With these goal in mind, here are eight design guidelines for Undashboards:

1. Reader comprehension

The Undashboard isn’t obsessed with cramming everything on one page. Modern web design has taught us to respect the value of white space, which gives people the opportunity to focus their attention and absorb information a morsel at a time. We’ve also learned that vertical scrolling isn’t evil. In fact, touch screens make vertical scrolling almost effortless.

An Undashboard takes its time to gradually display information, leaving plenty of room for white space.

This densely-packed dashboard pulls the reader's attention in every direction at once.

2. Data needs context

The Undashboard appreciates that data needs context in the form of related information and descriptions. Rather than squishing everything on one page, context can show up as details when items are selected and/or be displayed with graphical elements like color (as in the example below). Comparisons to benchmarks or goals are some of the most important ways to put data in context.

The colored metric bubbles indicate comparisons to goals while details on the right provide additional context.

3. Text is the glue

The Undashboard knows that presenting data isn’t just about data — the titles, descriptions, labels, and explanations are the glue that ties the data together and makes it truly readable. Good data communication requires a mix of clear, jargon-free language and the thoughtful focus on the most important data.

Careful use of text explains the data content.

4. Create a guided path

The Undashboard guides the reader through the content, rather than making readers find their way on their own. Traditional dashboards toss charts at a readers as if the order and relationships are meaningless. You wouldn’t scramble the paragraphs in a book if you wanted to tell a coherent story. The Undashboard uses an explicit path through the visuals to emphasize meaning and the author’s understanding of what matters in the data.

In its collapsed state, this application provides a structured, question-based flow to walk users through the data analysis.

5. Lead with a purpose

The Undashboard is designed with the end in mind. The purpose of presenting data is to help people be smarter in their actions. What’s the point if people aren’t going to do something with the data? The Undashboard leads users to relevant actions, which can come in many forms: discussions with colleagues, action plans, or direct integrations to other systems.

Embedded actions, like this "Create Student Group" button, makes for a short step between analysis and action.

6. Personalize the experience

The Undashboard is customizable for the different needs and interests of its users. The only valuable content is that which is pertinent to the reader. Many dashboards make the mistake of showing everything at once when the vast majority of the information is irrelevant for any individual reader. Undashboards makes the selection of scope a first-order, top-level feature. With the ability to present data interactively, you can give users control to choose what they care about, and free up a lot of visual space in the process.

This application provides ample opportunities for a user to choose what they care about:

This dashboard doesn't customize to meet the specific needs of a reader.

7. Start a discussion

The Undashboard recognizes that visualizing data is only the beginning. It should spark a discussion about what is happening and what to do about it. The data discussion that follows is the truly important part because that is when actual change happens.

Juicebox's discussion feature lets users capture, discuss, and share the insights they find in the data.

8. Form follows function

The Undashboard comes in different forms based on how, when, and why the reader is accessing the information. Dashboards can sometimes be considered the single form of output — the same things shown on the screen as is printed out or seen on a mobile device. Undashboards appreciate that the information and actions taken when someone is viewing on a mobile phone aren't the same as when projected in a conference room.

Fitbit's mobile dashboard

Like software in the cloud, it can take a while for many businesses to realize that the winds of change have already blown us a better answer. There should be no going back to static, dense, complex dashboards for communicating data. There are too many reasons why dashboards need to be transformed, including the needs of the users, new technologies, new design styles, and new understanding of how data can be embedded into business decisions. All of these factors demand a new future for dashboards.

Many of the examples above are created using Juicebox, our answer for building Undashboards. We'd love to show you how it works.

Putting People First in your Big Data Initiative

You have the resources and the data, but how do you package information so customers find it valuable? This e-book, Putting People First in your Big Data Initiative, summarizes how to make data valuable for customers. The focus is largely on those non-analytical audiences - the people that beg you for more information but won’t use your new dashboard. It also offers ideas on extending your Big Data efforts outside your organization. 

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The idea of putting people first goes way back to Zach’s Last Mile of Business Intelligence blog post in 2007, where he highlighted that the user experience is often the forgotten stage of any BI project. Fast forward to 2016 and the same can now be said for the Big Data project. The real value or monetization opportunity of these projects lies in making customers a big part of the success equation. Getting customers engaged, using your data, asking for your guidance and expertise should be the end goal of these projects. Given the investment and effort required to store, clean and analyze data, putting people first is a helpful reminder of where the finish line really is.   

You may not be ready to put people first now. There’s just too much messy data, too many tests that need to get run and too many new requirements to think beyond this week’s tasks. However, when you turn the corner and the conversation changes and you're ready to talk monetization, customer reports or data products, this document gives you the storytelling tips needed to develop an Information Experience that customers will love, so they clearly feel they were put first all along.

It's an easy read of 15 pages with plenty of tips, links and resources to help you be successful.   

DOWNLOAD EBook

People First Ebook Blog Post

The Cost of Status Quo

Three years ago when traveling in another city, you most likely called a cab and waited for it to show up. Today, you use the Uber app, request a driver, and watch it on the map until it arrives.  No more ride refusals, broken credit card machines, or mysteriously long waits.   The taxi system relied on the status quo for too long and now Uber is making them pay for it.  

Think about the information you deliver to customers. When was the last time it changed? Have you and your reports fallen prey to the status quo?   

Doing nothing is always an option, but it’s never a no-risk proposition.  At some point in time, the status quo becomes more risky. When it comes to displaying information for customers, here are some thoughts on identifying whether the status quo has become too risky and it’s time to make some changes.

User logins are on the decline.

Users are using the information you provide less and less. Perhaps they’re using another source or not using anything anymore. When customers no longer need what you provide, you’re no different than a taxi in 2015.

Reporting comes up during contract renewals.

hen a customer explicitly brings up reporting as a reason they’re considering your competitor or wants to see report changes before they’ll renew, it gets no more obvious than this. Unless you’ve stopped listening to your sales team’s voicemails then this is a direct indication that you’ve relied on the status quo too long.  The fact you’re still using voicemail might be a clue too.  

Ad-hoc report requests are increasing

A good indicator that you’ve relied on the status quo too long is that the amount of support calls from customers for ad-hoc reports is increasing. Often, part of the financial justification for moving away from the status quo is baked into your on-going support costs.  Keep an eye on the number of tickets/requests you’re getting.  

Sales team wants to understand reporting

This is usually a big deal when the sales team takes an interest in reporting because really, why should they?  This means it’s coming up  more frequently in deal discussions, or existing customers are asking questions. Changing your sales team is more expensive than updating your reporting.

You’re pushing Excel and PowerPoint to their limits

You're using all the advanced functionality, elaborate macros, and pushing the tools to their limit and it still doesn’t satisfy customer reporting requests. When customers see the hourglass more than the data, or you have to stagger how many emails go out at a time, it’s probably time for an alternative solution.

This may sound discouraging on many fronts, but have hope. If you see yourself in any or all of these points, it means that you’re not alone and there’s a solution out there.  It’s the season of giving, and being generous with our time (and opinions) is something we love doing. At Juice, we’ve actually done the homework on the cost associated with status quo reporting. Feel free to reach out to us or schedule a quick call. We’re happy to offer a little free advice and give you some options other than the status quo.   

Offer Self-serve, not Self-solve

Imagine this: after months of waiting for the new dashboard with promises of “actionable insight” and “democratized data” you click on the link and silence.  A numb feeling takes over as you stare  at the buttons and drop-downs as if they were from a commercial airline cockpit and wonder, what do you do with these fancy things do?

As the pace of business quickens, customers need data solutions that are truly self service and not self solve. Organizations continue to deliver solutions masquerading as self service, which offer extreme levels of flexibility and put the burden of solving the problem on the user. There is no service reflected in these solutions. A data product or solution should make the value of the data and how to answer a user’s questions readily apparent to truly be self service.  

Much of what we see in the consumer marketplace isn’t self-serve, rather it is self-solve. Take for example Trunk Club, an online men’s clothing retailer, where it asks customers a few questions about lifestyle, work-life, budget and sizes. Then, Trunk Club becomes their personal shopper and puts together wardrobe options, mailing them directly to the customer each month. This is a self-serve approach.

A self-solve experience, in contrast, will require more of your time.  The self-solve approach to clothing shopping is to turn buyers loose at the mall or on Ebay, where there is very little direction or guidance given to the shopper’s specific needs. Self-solve requires you to figure out the process yourself.   Self-solve involves an instruction manual or many rounds of trial and error.  

How do you know if your solution is self-solve or self-serve? Here are four clear points to help you distinguish the difference.

1. No Instruction Manual or Training Required. Remember the point of self-serve is to make life easier. Most users are not looking to invest more time, but less. Embed your training within the dashboard or application at key points.

2. Built to Answer Specific Questions. A self service solution is intended to answer specific questions. It’s not a means of just dumping information on someone.

3. Encourage vs. discourages exploration. While a long series of drop down menus may feel like it offers lots of exploration, it really doesn’t. Think of the paradox of choice. Offer a few options with interactivity, so the user sees immediately the fruits (or juice) of their efforts and wants to try more.

4. Make Steps Sequential. In the web analytics world you often want to see paths or steps the users took to make sure they’re guided down the intended flows. The same can be said for your dashboard. Make the flow or steps sequential and easy to follow.

What makes YOUR data powerful is creating an experience for the user that informs, instructs, and leads to smart discussions. Keep your audience engaged and deliver real value with a REAL self-serve solution. Don’t make them figure it out, because chances are, they won’t.

Review our design principles for a helpful guide and review examples of effective self-service models.

Schedule a demo to see how Juicebox can transform the information experience that your audience needs and values.

The Last Mile of Business Intelligence (Revisited)

Here’s another re-juice-inated blog post from years ago. Unfortunately, or perhaps fortunately for us, even after almost eight years, we’re still in the last mile. Even today, with Tableau’s huge success and so many data analytics startups, we still see organizations struggle to turn information into insights for their every day decision makers.

Here is Zach’s post from November 2007:

“The last mile” is a term that often is applied in the telecom industry in reference to “the final leg of delivering connectivity from a communications provider to a customer.” It is an expensive and complex step due to the challenge of pushing information from centralized, high capacity channels to many diverse end-points where information is ultimately used.

We think there is a “last mile” problem in business intelligence too. This critical bridge between data warehouses and communication of insights to decision-makers is often weak or missing. Your investments and meticulous efforts to create a central infrastructure can become worthless without effective delivery to end-users. “But how about my reporting interface?” you wonder. That’s a creaky and narrow bridge to rely on for the last mile of business intelligence.

Listening to our clients, we are confident the last mile is a real problem. The ultimate source of this failure is less clear. Here are a few of theories:

1. The engineers who built the data warehouse build the interface. No offense to the talented individuals who can push around, clean, normalize, and integrate data—but they may not be ideally suited to designing a user interface for non-technical users. A designer wouldn’t create charts that look like this (our favorite example of chart-based encryption):

In the worst case, developers are dismissive of user experience. I’ve met with IT folks who felt confident that providing a massive data table would provide a suitable solution for delivering information to users. “Hey, they’re getting their data. Is there a problem?”

2. Reporting is considered the fundamental mechanism for working with data. Here’s a framework we’ve started to consider in thinking through the multiple approaches for getting value from data:

• Reporting lets you monitor things that are well-understood and relatively predictable.

• Exporation or analysis helps you understand new processes and erratic and shifting behaviors.

• Presentation is about communicating insights and understanding, often building on both reporting and analysis.

Many people assume that a reporting tool is sufficient to do in-depth analysis and communicate results. That’s like trying to build a deck with a screwdriver.

3. Poor fundamentals in information display. Despite the efforts of folks like Edward Tufte and Stephen Few, general literacy in this area is still low. Shiny, 3D pie charts are still acceptable, even desirable in some places. Particularly disturbing is the persistence and pervasiveness of this problem in Excel where there still remains some confusion as to why this is bad information display:

You don’t have to go any further than the Dashboard Spy to find examples of the visual muck that is commonplace.

Statisticians & Storytellers

We decided to refresh and re-JUICE-enate a blog post that Chris wrote in 2005.  Click here to read the original.

The way the game of analytics is played today, there isn’t much competition. The statisticians are on the field, the storytellers are on the bench—or in the stands—or, sometimes, not even in the stadium.

We first expressed this sentiment almost a decade ago, but in the last ten years not much has changed. There may be a lot more players, and there is definitely a lot more data, but statisticians and storytellers still aren’t playing on the same field together.

In Chris’ earlier post we proposed that the answer to getting statisticians and storytellers to work together lay in the visualizations themselves. We still maintain that’s true, but believe that there is a bigger emphasis needed on storytelling and fostering discussions among people about data.  While visualizations were relatively new ten years ago, today every CFO around the world has already approved their first visualization purchase order. Unfortunately, there’s too much focus on charting capability vs. bringing these teams to together to solve real business problems.  As Chris stated 10 years ago, visualizations should be designed not to just reflect data, but to engage the user with a story. When visualizations are approached in this way, it provides the perfect environment for statisticians and storytellers to collaborate and succeed.

At Juice, we’re now ten years into our story, we continue to help organizations bridge the gap between statisticians and storytellers. To learn some of the recent stories check out the case studies on our travel and hospitality, digital advertising, research, and healthcare solution pages.  Give them a read and share your story in the comments below.

The Myth of Flexible Reporting

Flexibility is essential, no doubt, to navigate life and work. Yet, flexibility is not always what is needed. Take for instance this NY Times Article, Too Many Choices: A Problem That Can Paralyze, which states that when we are faced with more options we tend to shut down or make decisions against our best interest. Often times, especially when dealing with data or making decisions, more flexibility is less helpful. It actually works against us in terms of work efficiency and cognitive load. When displaying information to the everyday decision maker, offering them the single best raisin bran choice vs. a list of choices is always best.

So what does this mean for your information sharing and reporting? Does your audience really want more reports or additional download options?

The answer is no. The myth in the reporting and dashboard world is that customers need or want more analytical flexibility and data. Sure there’s always some analyst that REALLY needs it, but more likely your buyer or end user wants your guidance on how to consume the information.   More choices always feels like a good idea on the surface until you begin to see the breakdown that occurs with users when they are drowning in reports or giving your interface that deer in the headlights stare. More reporting flexibility equals more support calls, more report requests, etc.

Here are a few reasons why your users might ask for more flexible reporting options. Be aware this is a HUGE opportunity for you to demonstrate your expertise with the data and guide them down the right path.

#1 Uncertainty - Your users aren’t really sure what they plan to do with the data, don’t know the problem they plan to solve or their business direction changes so often so they figure they need flexibility. This is an opportunity to show them the value of what’s in your data and the types of problems that can be solved. Provide certainty through instruction and guidance vs. feeding the uncertainty. This is a perfect opportunity to be a hero for customers like these.

#2 - Only one Shot -  Whether real or perceived, your customer perceives they only have one shot because of project timelines or budget reasons to solve for everything they need for the next 1+ years. In this case you need to teach them to be gourmets about the data and not think of it as a Vegas buffet. Getting every last bit of data won’t solve any problems. Help them solve a specific business problem with the data, in a timely manner (weeks not months). They will then have the credibility and leverage to ask for more resources. They’ll also have you to thank for it.

#3 - Do it myself - Do it Yourself (DIY) is fine. If they’re experts on your data and you have confidence in their capabilities and ability to come up with the right interpretation then let them go. However, be careful on this one. Often times it means that they don’t trust you to explain, guide or provide them the data they need or have asked for. Be sure to probe on this.  Has it happened right after you delivered a new set of reports? There are risks here of them coming up with the wrong interpretations or worse yet, you’re just a commodity provider of data.  

The place you want to be is like a personal shopper. You recommend, guide and instruct your users to the best path for them. If you just give them the cereal aisle, you’ll only be a cashier.  

When you guide them they know you care and are taking a REAL stake in helping them. Avoid the myth of flexible reporting. Check out Juice’s design principles, specifically the ones on guidance to offer up some ideas on how to implement guidance. As always, feel free to drop us a note with your thoughts or questions at info@juiceanalytics.com or tweet us @juiceanalytics.com.

Metrics that really matter - common pitfalls to avoid

No matter what business you are in, keeping a competitive edge is essential. Being able to evaluate your performance and extrapolate the next steps is essential to a successful  business model. Just like a judge at the Westminster Dog Show, you will need a host of metrics to scrutinize a good performance.

So what is the key to winning in the dog-eat-dog world of business? Tracking and analyzing of metrics, of course. Your metrics can create focus and alignment in your company by providing clarity to what improvement looks like. Although be warned, they can also lead a company astray if not carefully selected.

5 Common pitfalls to avoid when choosing metrics:

Historical conventions translate into blindly following conventional wisdom or history without giving thought to the implications. In an ever changing business climate, you stay on top by being adaptive and responsive.  A Westminster judge is not going to vote for the posh poodle just because the previous two winners were poodles.

Simplistic metrics means taking only at face value what data gives you. Just because the data is easy to track does not mean it will lead your business to the front of the pack. For example, in a two day dog competition with many different breeds of dogs, easy to obtain metrics like weight and height, would not be enough to help you discern a deserving winner.

Complex metrics are contrived metrics that combine data from many sources. If your goal is to shape company behaviour to increase success, then it is imperative for people in the company to understand how the metric was created and trust the data source. Otherwise they may be skeptical of the metric. The metrics for Best in Show are transparent for all involved. This is imperative when you are dealing with dogs of all shapes and sizes. The dogs are first judged within by metrics within their breed. As the competition continues grouping is based on the jobs the dogs were bred to do.

Too many metrics, also known as data overload. Typically, this occurs when you are working with dozens of key metrics because they all mean something, but they may not all deserve to be called “key”. This is why grouping and filtering down is important.  If you a had to choose the winner of Westminster on day one with all 2,500 contestants present, that would be overwhelming!

Vanity metrics are just what you think they are. These are the metrics that make your organization look good, but don’t necessarily tie to important or relevant outcomes. The dashing dachshunds might look dapper on the runway but how well did they perform in the other areas of competition?

By avoiding these pitfalls, you can create data products that will lead your team to meaningful decisions and actions.  Accurate tracking of data and analysis is the key to your company unleashing its earning potential and staying ahead of the competition.

Find out more about effective data visualization from our book, Data Fluency.

Get a free excerpt from the book! (enter code: FLUENCY-EXCERPT)

Excerpted with permission from the publisher, Wiley, from Data Fluency: Empowering Your Organization with Effective Data Communication by Zach Gemignani, Chris Gemignani, Richard Galentino, Patrick Schuermann.  Copyright © 2014.

Goals and Metrics, like Peanut Butter and Chocolate

Goals are defined by metrics. Metrics are given meaning through goals. They go together like peanut butter and chocolate.

That’s why we decided to integrate goals into our customer reporting and data visualization platform, Juicebox. To help people make better use of data, we needed to think about how people set, track, and update goals. In the process, we tried to answer the why, who, what, how, when, and where of using data-driven goals.

Why do we set goals?

Goals help focus an organization and connect everyday activities to a larger purpose. Goals are a communication mechanism to emphasize what’s important. They define the gap between the way things are now and where the organization wants to be. Goals establish priorities.  

Who sets the goals?

Commonly, goals are set by the highest level of management and passed down to the rest of the organization. However, its not unusual for management to be disconnected from the constraints and realities of the metric and goal. The best people to set goals are those who know the context, can be accountable, and have access to the resources to impact change. It is also important that there is transparency in who set the goals and why it was defined as it was.

"The early models (some still common today) focus on management. Goals are established by top executives and then communicated down into the organization. Therefore, goals are not always meaningful to individual contributors and employees doing the actual job." - Goal Science Best Practices, BetterWorks

What is a well-defined goal?

A common framework for setting goals is the SMART criteria. Goals should be: Specific, Measurable, Achievable, Relevant, Time-bound.

via http://iqdoodle.com/smart-goals/

How should we set goals?

A metric-defined goal needs to find a balance between realistic improvements and previously-unattainable ambition. Finding this range requires analysis. Consider industry averages, historical performance, and expert opinions. Top performers can lend guidance as to what’s possible but extreme outliers will set an unrealistic bar.

When should goals be evaluated and re-evaluated?

Choosing when to update your goals depends on the pace of your business and how quickly you can track progress. You want to update goals as conditions change and as you bring in more information to know whether you’re expecting too much or too little. At the same time, goals without some sense of permanence are easy to ignore. Practically speaking, many organizations are evolving from annual goals to quarterly reviews to ensure better responsiveness to changes.

Where should goals show up?

Our Juicebox platform enables the kind of interactive reporting that people can actually understand, use, and act on. To make data more useful, we knew it was important to allow our customers to build goal-setting right into their apps. We paired our visualizations for showing key metrics with an expandable drawer to let users set their own goals.

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Here’s what we did to implement a feature that would make goals part of everyday data usage:

1. Enable permissions to allow specific user types to have the ability to set goals. The rest of the users see the goals but can’t make changes.
2. Goals are paired with information about the key metrics (e.g. comparison to industry average, trends) to guide SMART goal-making.
3. The user-defined goals become an integral part of the report — not only are key metrics compared to the goals, but other results throughout the interactive report are keyed off the goal.
4. Enable collaborative discussions about the goals right inside the Juicebox application.

To get a better glimpse at Juicebox and the goal setting features, schedule a demonstration via this link.