Archive for Presentation

Developing Meaningful KPIs to Get More from Data Analytics

As the days grow shorter and end of the year lists start appearing in our feeds, it’s natural to take a retrospective view on the past year and to begin thinking about what we could do differently for 2018 regarding data analytics.
Where do you want to be at this time next year? How will you get there? And how will you measure your success?
Now is the time to form meaningful key performance indicators (KPIs) that will guide you through the coming year and have your association meeting its goals.
Association Analytics COO Julie Sciullo, along with Sean Hewitt, our Director of Data Governance and Adam Rosenbaum, Director of Information Systems at CASE—will be presenting on this topic at the ASAE Technology Conference in December.
Here’s a sneak peek of what they’ll cover in their session and some tips on how to use data analytics to build useful KPIs.

What Are KPIs?

A KPI is something that can be counted and compared. It provides evidence of the degree to which an objective is being attained over a specified time.
For instance, if your goal in 2018 is to raise the public awareness of your association, then KPIs might be to run X number of ad campaigns that received X number of impressions in the first two quarters.
Here are some questions to ask to determine if the KPIs you have are working in the right way:

  • Can it be counted in the form of a number, percentage or currency?
  • Can it be compared to what is optimal?
  • Is the evidence observed in the same way by all stakeholders?
  • Is it contributing to a significant organizational objective?
  • Is it being measured over a specified period of time?

What Makes a KPI Meaningful?

A meaningful performance indicator ties directly to a strategic objective. Though keep in mind, making the connection between an ambitious objective and winnowing it down to a measurable indicator that’s manageable and measurable is not always an easy task.
If only it were as simple as telling a team to climb up a hill, where you have a precise, calculated performance metric. As you progress up the hill, you can track the distance travelled, the number of teammates who are still climbing, and how far left you have to go. At the end of the journey, you’re either at the top and you accomplished your goal, or you fell short.
The objectives your association wants to achieve probably aren’t as literal as mountain climbing, but it’s worth taking the time and mental effort to figure out what hills you want to climb and then breaking the journey up into measurable pieces.
In the end, the meaningful KPIs are those that move your mountains into molehills, breaking up the bigger goal into attainable chunks that can be effectively measured to make sure you’re on track and that the actions you’re taking are having a positive effect.

How Can Data Analytics Help Inform KPIs?

A meaningful strategic goal (and the KPIs that correspond to it) balances on three important points: strategy, data, and the ability interpret that data. What ties it all together and really allows an organization to take action is understanding what you want to get out of accomplishing that goal and why you want to accomplish it in the first place.
Using and analyzing data to define your strategy takes away assumptions and cuts to the center of the goal’s purpose. When you can look at what the data is telling you and combine it with the “why” of your goal, you can better define the next action steps to take.


Interested in learning more about our session at ASAE Tech or how data analytics can inform your strategic goals? Sign-up for our monthly newsletter.

Storytelling with Data

I recently had the opportunity to attend a workshop called Storytelling with Data by Cole Nussbaumer Knaflic. Instead of focusing on data analytics tools, the workshop focused on using data as part of the storytelling process. We reviewed the fundamentals of data visualization and how to communicate effectively with data.
Here are five steps you can take to tell a story with your data.

Step 1. Give Your Data Context

After you have created your exploratory analysis (identifying interesting things to learn from your data), you can move to explanatory analysis (communicating these findings to someone else).
Just like in other forms of communicating, you need to think about your audience and the message you want to convey. You will need to understand the current situation.
Low tech storyboarding can be used to plan out your communication plan. The risk and impact are lower at the beginning if you need to modify your plan to ensure that it is clear.

Step 2. Choose the Right Visual Display

Choosing the most effective chart type for your data is important. There are no hard and fast rules but there are definitely guidelines.
We’ve discussed choosing the correct chart type before, so this part of the workshop served as a reminder to be deliberate in choosing the correct chart type for your data. Here’re some blogs we’ve written on this topic before: Powerful Visualization Choices (Part 1), Part 2, Part 3, Part 4.

Step 3. Declutter Your Viz

This is a step that it may be easy to skip, but it is one that will take your chart from drab to fab!
Take a hard look at the visual you created. You want to ensure that each element on the chart has a value. Think about chart borders, gridlines, data markers, axis labels and legends. Each element on your chart adds to the cognitive load for your audience. We want to make it as easy as possible for them to concentrate on the data story you are trying to tell, not spending energy trying to decipher all the visual cues you are throwing at them.
cluttered-line-graphline-graph-clean
Here, Cole explained that we should consider the Gestalt Principles of Visual Perception which explains how people interact with and create order of out visual stimuli.
It was very interesting to see how the principles aligned with my experiences. Cole’s book explains this better than anything I could find elsewhere, so I guess this is my plug to buy the book!

Step 4. Focus Attention on the Key Parts of the Story

All good stories have the main characters and a central plot.
Once you have chosen the correct chart type and reduced clutter, keep thinking of the audience and the story you are trying to tell.
Here we learned about preattentive attributes (size, color, and position) and how to use them to focus attention. Our brain is super quick at picking up on preattentive attributes and we want to use that to our advantage.
These attributes should be used sparingly and purposefully. For example, don’t use color just to make it colorful. Use color to direct attention to what you want the audience to focus on, such as lower than acceptable KPIs or better than expected renewals in a member segment.
One simple exercise you can do is to ask a coworker or friend to look at your chart ask them where their eyes go first and where it is drawn. This can help you confirm that the chart you’ve designed is drawing attention in the way you expected.

Step 5. Tell Your Story

Once you have your beautiful charts, you need to think about how you will convey this information to your audience. The advantage of a story is that it sticks in our memory and can be retold. This is important as we seek to persuade others to see our point of view. You also want to use texts, labels, and action titles within your presentation. Just like your favorite movie or children’s book, think about how conflict and tension can be used when telling your story with data.
One technique I really liked was building the visual as you talked. For example, during an in-person presentation, have a slide that only shows the title and axis, then builds in the legend or categories. This allows you to explain your chart without having people focusing on the data yet (tension and suspense!) and then hit them with the data. You can even build the data in by showing past history first (context) and then showing current information.
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What Would Your Members Write in a Postcard to You?

Dear Data

Have you ever heard of a book titled Dear Data? I first learned about it from an article in Wired magazine.  The book is not a story, but rather a collection of postcards written between two information designers who communicated in data.
Giorgia Lupi, a resident of Brooklyn whose native tongue is Italian, and Stefanie Posavec, a resident of London who speaks English, first met at a design conference in 2014. At that time, they wondered if they could get to know each other through data without speaking the same language. They proceeded to find out by mailing each other postcards for 52 straight weeks expressed as visualizations.
Each week was a new theme extracted from daily life, such as sleep habits, spending habits, checks of yourself in the mirror, and number of times saying thank you. The book compiles all 104 postcards and positions them side by side with an explanation of each.
You can preview several pages of the book here, and it is absolutely fascinating to see how the same topic can be communicated differently, the way everyday life turns into a visualization, and the detailed artwork on these postcards.
The complexity and mundanity of everyday life jumps off the pages and the legends for interpreting each could definitely get you thinking creatively about new ways to visualize your own data – or life.

Counting Something Means It Matters

The best summary of the book is a quote from Lupi, “counting something means it matters.” Think of all the things you could count about your members. What could you discover about how your members engage with your association?
Let’s take it one step further. If your members sent you a postcard every week for one year with a data visualization about their lives, what would the postcards reveal about them, their interests, and their relationship to your organization?
Would your association play a prominent role in the narrative? Would you discover untapped areas of their lives where your organization could add value?

Data Analytics

It is unrealistic to ask your members to send weekly postcards, but you can use data analytics to visualize and understand your members and their journeys.
Pulling from data sources like your website, your AMS, and social media, you can paint a complete picture of your members. When we understand our members and customers, we can guide them along a more personalized journey.
Whether through postcards or data analytics, you can get to know somebody through data and that insight can help you better serve your members.

How to Succeed with Data Analytics

If you’ve ever participated in a data analytics implementation, you may be familiar with the indescribable excitement around the project. Who wouldn’t be eager for a solution that makes it easier and more efficient to understand and serve your customers?
But what happens after excitement of your initial implementation fades, the consultants have gone home, and your dashboards have lost their shiny, new appeal? How can you ensure a return on your investment?
Recently, Galina Kozachenko (Association for Financial Professionals) and Debbie King (Association Analytics) discussed the afterglow of data analytics as part of the weekly Association Chat series hosted by Kiki L’Italien. You can replay the recording here. Here are my top 5 takeaways for how to succeed with data analytics:

1. Align Analytics with Association Strategy

What gets measured, gets done. “Analytics and strategy need to live side by side,” said Galina. It’s important that for every strategy, you have a hypothesis that’s tested by measuring and tracking defined metrics.

2. Manage Your Scope

Don’t start too big. “We have seen the greatest success when an association starts out by analyzing one area at a time,” said Debbie King. Prioritize your business areas and ensure successful implementation of one area before moving on to others.

3. Establish and Enforce Data Governance

Data governance is elusive, but attainable if you treat data as an enterprise asset that is the responsibility of everyone. Galina recommended evaluating your data early in any analytics engagement to better understand what elements will need to be kept clean in the future. Read more about data governance.

4. Identify a Data Champion

One of the most important factors in successful adoption of a data strategy is having one (or more) data champions. These internal staff members are able — through influence, education, or example — to advance the cause of data throughout the organization.

5. Be Prepared to Manage Change

Data analytics is an exercise in change management and that change won’t happen overnight. “It’s not a one week journey,” said Galina, “but once the traction picks up, it will be like a self-propelling train.”
To help ensure adoption, you need the support and buy-in of leadership and staff. Communication throughout the project is key. Be prepared to continuously demonstrate value through “quick wins” and sharing success stories. Your data champion or analysts also will need to commit to spending time training, providing analysis, and working with both the early adopters and the risk-averse.
Debbie recommends publicizing and promoting internal data analytics work in much the same way you would promote an external benefit to members. Pick an area and provide a weekly summary to leadership about the meaning of “story in the data”. Encourage the analytical mindset by having a “Question of the week”. Look for and show examples of surprises in the data that defy intuition. Increase visibility and stimulate interest by placing a monitor in the kitchen or lobby that shows high level visualizations that rotate each day.

failure-quoteGiving Up is the Only Sure Way to Fail

Ultimately, though, success isn’t even possible if you don’t try. “The only time you can really call an analytics initiative a failure is if you give up,” said Debbie. “It’s an iterative process and the most important thing is to get started where you are.”

Association Leaders and the Analytical Mindset

In April, I had the pleasure of speaking with a group of aspiring association executive leaders as part of the “Through the CEO Lens” series about how leaders of the future will increasingly need an analytical mindset. I was joined by David DeLorenzo with Delcor. You can view the recording below.
What is an analytical mindset and why is it important for leaders to have?
Association leaders today have more decisions to make and less time to make them. Having an analytical mindset – the ability to understand, visualize, and communicate data – will be the most important leadership skill in the next decade. When leaders understand the story their data is telling, they can leverage that knowledge to make decisions with confidence and shape the future for their organizations and their career.