Driving Actionable Insights Through Data Engagement

By Rusty Rahmer

How Companies Can Get Data Fit

Rusty Rahmer has over 17 years of experience driving digital strategy, technology program planning, and delivery in financial services and health care. Since 2013 Rusty had been leading enterprise class digital intelligence programs at investment company Vanguard and more recently at pharma giant GSK. In this post Rusty relates to a challenge many analytics professionals have faced - _“We’ve built this great dashboard/platform, how come no one is using it?” _At the same time in a boardroom nearby an executive leadership team is discussing why their multi-million dollar investment in data and analytics has had little positive impact on company profits.

Rusty walks us through a similar experience from his career and how together with his team they developed a methodology to increase stakeholders’ engagement and bring about a complete transformation in how data was viewed in the company. This framework is still in place to date, several years following initiation

Problems With Engagement

Over the prior 3 years we had completely revamped our digital intelligence program; procured and installed all best technologies, built analytics teams in each business line staffed with top analyst talent, and built an enterprise-wide Center of Excellence to support the practice and thought leaders. As a result, we had more meaningful higher quality data flowing than ever before and yet, no one was using it. The data, analytics, and insights the teams were pumping out were being distributed and summarily ignored. Executives were seeing more data cross their desks but starting to question why we weren’t seeing more impact, was it the investment, the strategy, the implementation, the talent? The cry for “Actionable Insights” was starting to grow.

As the team leading the program, we’d reflect and admit it took longer than expected to build everything out, but we also knew (or at least, felt) that we had made all the right moves and were right where we wanted to be, but the Execs were correct, something wasn’t right: the business wasn’t engaged.

Once we finally saw the engagement problem, we couldn’t un-see it. From the emailed monthly reports that no one opened or read, to the elegant Tableau dashboards that no one interacted with, to experimentation teams with no backlog of ideas to test, the problem seemed to be everywhere we looked…hours of talented analyst work going unused!

As a leadership team frustrated by our revelation (and over a few somber drinks) we’d develop the analogy that it was like the business bought an incredible home gym with all the best intentions of becoming fit, but wasn’t bothering to actually use the equipment. Together we’d lament about “How can they (the business) expect to get in (data) shape if they treat the analytics team like the gym equipment sitting in the corner of their basement?”, “Don’t they understand they need to use it? Engage with the data?”, and finally someone said “It’s like they need a trainer”… and there it was… the answer!

Analytics in Action

Our team took to developing our new service offering beyond the analytics, the tools and capabilities. We set out to devise a way to train our business partners on how to engage and derive business value (action) from all the new incredible analytics capability that they now had at their disposal. We took a few minutes to outline the goals of our new service:

• Set the local business analytics team up for success (not ourselves)
• Establish a durable process the local analytics team can own
• Engage the business with a cadence they can sustain and commitment to
• Demonstrate how data/insights can power business action and activity. Show them INSIGHT to ACTION!

We called our new service Analytics in Action. The concept was simple - partner with the local business analytics team to host and co-lead a monthly analytics read out, an Analytics in Action meeting, with key leaders, stakeholders, and partners from the business. During the meeting, the local analytics team would present analytics from the prior month’s performance and be prepared to highlight a few interesting data points as fodder to create a conversation and we would help steer the conversation, translate the dialogue into action items, and define/assign follow up.

The real magic of our exercise was a combination of the facilitation of the data engagement by asking questions like “Why do you think that is?”, “Do you think we should take a closer look at that?”, “What does that imply we would do differently?” and “Is that something we should try?” then physically writing those ideas down and placing them in large jars boldly marked with categories like “Test and Experiments”, “Take a Deeper Dive”, “We Should Collect This Data”, etc.. The big jars and brightly colored Post-it notes were purposeful and designed to be bold, highly visible, physical manifestations of the conversation translating into action. The jars were being filled with Actionable Insights.

We tested the Analytics in Action format out with our first business team as a pilot. Armed with our brightly colored Post-it notes and action jars,the first meeting happened with two of our key team members facilitating the discussion and the rest of us desperately waiting to hear how it went. When the meeting ended, our colleagues inside the room sent us a text with a picture of the attendees/leaders inside the room huddled behind the jars full of Post-it notes! With more than 33 Post-it notes filling the various jars in just an hour and a half of conversation, the exercise was a smashing success. The business team loved the exercise!

Over the next few months we formalized and rolled out the Analytics in Action (AinA) meetings across all of our internal business teams. After a few iterations of the process, we documented the best practices into an AinA Meeting in a Box. The tool kit literally included a large clear box full of meeting materials including the jars and plenty of brightly colored Post-it notes. The meetings were a welcomed and popular success with the business and dedicated analytics team. The business teams loved seeing their ideas channeled into action and the analytics teams loved the engagement in their work.

When we checked in a few months later, after turning over the facilitation of the meetings to the local analytics teams, we found the meetings still happening on a regular basis (some had even increased frequency) with high attendance and incredible engagement. We found experimentation with backlogs of ideas for testing, and we found analytics teams with high engagement and satisfaction in the impact and value their work was having in shaping the direction of the business. Finally, perhaps most important was what we didn’t find… gone were the days of dissatisfied business leaders asking for more “actionable data”… now they had it, and they could see it… in motion.

The next section is the Analytics in Action best practices document we used to facilitate our meetings. We recommend you follow these steps to begin building engagement and getting your organization data fit. One good sign to look out for is the desire for participants to want to include others. It’s a good litmus test to gauge if the meetings are valuable to the audience. And most importantly, focus on empowering your local analytics team to run and take credit for the exercise.

• Start small, with a pilot.
• Don’t overload the room.

Analytics in Action Guidelines (Meeting in a box)

Overview

The purpose of the Analytics in Action (AinA) meeting is to generate engagement with data and to channel the ensuing discussion into actions that can be assigned, tracked, and followed up on.

• Jars are used as physical and visual manifestations of insight to action.
• Success should be directly measured by the number of items collected in the jars.

Who Should Attend

The meeting should not be considered exclusive. Ultimately, all are welcome, but with a few considerations:

• Senior/Executive engagement in AinA meetings is critical.
• Start small and build momentum before increasing audience size.
• Most successful meeting outcomes include:
  • Active Participation
  • Innovation
  • Multi-disciplinary audiences

Frequency

We recommend a monthly frequency for must business scenarios.

Key Roles

The following roles will need to be accounted for. In some cases, one person may fill more than one role but one to one alignment of person to task is proven to be ideal.

• Sponsor – The person who is sponsoring the discussion, and is ultimately the owner of the audience, scope, and direction the monthly meeting takes. There will also be times when decision making and/or prioritization is required: this person should be in a position to be responsible for these decisions. Suggested persons: Senior Leader of Analytics in the Department, Head of Marketing, etc..
• Host – The person who will kick off and facilitate the majority of the discussion. Be a catalyst to getting the attendees involved and generating ideation from the group.
• Analyst(s) – The person(s) who has done the data prep work that will be shared with the group and considered the foundation of the discussion.
• Journalist – The person who will capture the actionable tasks, assign them to the appropriate jars, log and communicate all collected actions and assignments to the attendees post meeting. The journalist will also start every meeting by facilitating updates from appropriate owners of the action items assigned to them in prior AinA meetings.

Note: Though primarily the Journalist’s responsibility is to log the actions and assign them jars, it will be a shared responsibility of the Host and Journalist to foster and translate the loose group discussion into structured actions. How this is handled during the session is critical and should be worked out prior to the meeting. Great discussion with no action items in the jars is failure. Likewise, action items in the jars with no engagement from the group is also failure.

Jars and Descriptions

• Take a Deeper Dive
  • Probably not worth being on the dashboard and monitoring monthly but we should dig in and understand it
• Tests and Experiments
  • Let’s try this idea and see if it works!
  • Ways to learn if it’s A or B that’s driving the data we’re seeing
• Not sure About That Data
  • Let’s validate that what we’re seeing in that data is correct
• Add That to the Dashboard
  • This is something we should track and monitor monthly
• We should collect that data
  • Things that should be tagged
  • Data integrations
  • Other data sets to discuss

Structure

1. Meeting Kick-Off
   • Explain the goal of the meeting
   • Orient participants to the jars and kinds of things that go in each
   • Introduce the analyst
2. Updates on action items from last meeting (if this is not the initial AinA meeting)
   • Read through action item log and have owners provide status updates
3. Data Review and Discussion
   • Lead the discussion through the data
   • Facilitate actionable task collection and classification
   • Generate engagement and participation
4. Closing
   • Thank the audience for their participation and ideation
   • Comment on the amount of action generated from the analytics and discussion
   • Explain what will happen with what has been collected
     • Each item will be logged in a spreadsheet
     • Assigned an owner
     • The next meeting will start with updates from the items collected
5. Post-Meeting Follow Up
   • Log action items in with previously collected
   • Assign ownership
   • Email/Communicate new and outstanding items to attendees
   • Thank everyone again for participation and highlight the number of actions opened and closed to date as a byproduct of the AinA meetings.

Written by: Allen Hillery
Reviewed by: Matt David