Data + Communication Skills = Credible Insight for Decision-Making Conversations

By Mark Roberts

Data-driven story creation is growing! Data's role in the production and distribution of information captures attention and bolsters your credibility as a trusted advisor with your customers. However, as someone who has seen the glazed-over expressions that can occur during the recitation of pivot chart slide number 20－what matters is the ability to craft a good data driven story. It's very easy to inadvertently lean too heavily on the data resulting in a disengaged, unconvinced or confused audience. 

With data storytelling, you are communicating a more meaningful message, and as with any riveting story, you are delivering a message that offers a critical insight or a surprising result. The skill that is required to recognize an insight or a finding －matters just as much as the ability to share statistical validity. These skills are similar to those of an excellent communicator or dare I say, marketer: knowing how to write a key message, how to identify and target the audience, how to tie the message to a financial outcome and ensuring a quality deliverable.

When you are telling a story with data, please remember that not everyone is a 'numbers' person. To some members of your audience, their freshman statistics class may have been a nightmare. Accordingly, tell your story in words strong images and numbers. Make your key points in a bulleted text followed by an expository chart. The chart should be easy to read and contain prompts－such as highlights－about how to read the data. I've worked with analysts who test their tables by showing them to someone who is not familiar with the subject. If that person is confused, you still have work to do.

As shared in an excellent article by  Olivia Par-Rud:     

“As a Data-Driven Leader who champions Data-Driven Decision-Making, you must be able to effectively communicate the power of your insights and strategies to your team members and stakeholders. This requires knowing the perfect level of detail for each unique audience.”

Recently I had a conversation with a profit specialist about how she presents data to her clients. Interestingly, she doesn't consider how she preps and presents the data as creating a narrative－however that's exactly what she's doing, instinctually. 

The overall purpose of the project we discussed is bottom-line performance improvement. In short, the IMs job is to be a profit specialist and ensure that her client gains as much margin as possible while mitigating profit leakage. To drive results this process must be collaborative, so they often schedule quarterly meetings to evaluate the profit journey and adjust as needed. The purpose of the evaluation is to look at trends for sales and margin, uncover profitability leakage, and to present opportunities for further prescriptive activities to drive more profitable results. Her audience is the pricing committee and senior management. Here are the steps she goes through to prepare and present the information:

●     Know your audience and what keeps them awake at night- profit specialist knows her audience is the client's pricing committee and management team. Their concerns are improving profitability, reducing profit leakage, and finding new opportunities for profit optimization. Sales leaders want actionable data in the form of dashboards that quickly tell a story so sales can have meaningful discussions with their customers.

●     Frame the subject and purpose before the meeting-As mentioned above, the meeting is communicated as a business meeting where she reviews monthly trends for sales, margin, uncovers issues, and presents further opportunities. Prior to each discussion she checks with leaders to ensure she is aware of their current key objectives and any new challenges that may have occurred since the last meeting.

●     Knowing what not to show is as important as what to show- Her reporting tool's dashboard provides a massive amount of data and ways to slice and dice the data. So, when she is prepping for these reviews, she likes to pull out a few successes and a few areas that need improvement. Otherwise, she finds the discussion exceeds the scope and goes down rabbit holes that do not serve the customer’s goals.

●     Show the data in an easily digestible format- The profit specialist uses a diagram that she refers to as an 'aha chart,' also known as a histogram. A histogram is a graphical display of data using bars of different heights. The difference between a bar chart and a histogram is that histogram groups numbers into ranges. The height of each bar shows how many of the variables fall into each range. 

●      Discuss the data in terms of what your audience understands- In her client's histogram, she organizes all the purchase orders into gross margin 'buckets.' She confirms that looking at the data in this way 'tells the tale' of how the client's staff think and how they price items.

●      Ask leading questions and provide commentary to drive the conversation- The profit specialist asks a series of questions and comments that are partially rhetorical to engage discussion and discover the 'whys.' For example:

●      Is the client at market-level pricing, or are they defaulting to a single margin? (Meaning do they add X% margin and call it a day.)

●      Are the salespeople negotiating because a 'peanut butter' margin could mean there is no negotiating behavior? To an analyst 'spreading peanut butter pricing' means to apply a single margin and spread it over the cost of every product and client like spreading peanut butter across an entire piece of bread. For instance, every client gets 20% off every product.

●      The biggest bar may indicate the team uses one (favorite) margin percentage. Is this true? How did they determine this target margin verse strategic price?

●      Are there are spikes of transactions at increments that end in 0s and 5s? Consistent spikes at 25%, 20%, 15%, and 10%. These factors could indicate how the team lowers price/negotiates. For instance, A customer requests a quote, the sales rep quotes a price, the customer says "you have to do better than that," the rep cuts 5%, the customer says, "hmm you still need to do better", the sales rep takes another 5% off, the customer pushes back again, and the 5% reduction ( what we call profit bleeding) continues. 

●      Allow space for the audience to 'help' with the conclusions and manage expectations- Uncovering and presenting these trends to the client brings awareness to the team to help guide them to want to collaboratively drive improvement. Most clients are astounded when they look at their data in this way. We believe that for a few reasons. First, it is THEIR data, not some industry analyst survey. Second, it sparks a lot of dialogue drive by data insights.  

●      Once the client reacts to the data; show them a solution to their problem(s)- If a client wants to be a more profitable company, they need to move the team off of the default margins and cost-plus methodology and utilize strategic pricing. Essentially, they need to understand that not all customers need to be priced the same and not all products should be priced the same. You can't fix what you don't know. So, if a client doesn't know that their team (or an individual) has a favorite margin, they don't know where to start taking action. 

The ability to provide advice and actionable insights is the last mile for data science. The solution is data must be used to support storytelling for a compelling and credible narrative that delivers the information these decision-makers want and need. 

The story must be crafted leveraging actionable data recognizing your audience and their key goals and objectives. When this is accomplished the conversation becomes collaborative and the profit improvement journey plans is launched with specific strategies and tactics to drive the maximum impact with the least risk. (yes, your data can tell you the least risk actions too)

How well does your team share data stories?

Are your salespeople training and equipped with tools to have insightful business conversations?

How often do you consider the audience when shaping your data driven story?

Does your team consider the audiences skills and understanding when shaping their data driven stories?