Data storytelling is this super trendy, super buzzwordy thing in the tech industry right now, and frankly, I’m done with it.
Why? Because literally NO ONE saying they are doing data storytelling is actually doing it!
Data storytelling experts lead us to believe that the tools we have today are as good as it gets. If we couple these tools with well-trained people who can do helpful, visual tricks and create better Powerpoint presentations, we’ll be able to get our data insights across to the people who need them to make decisions. And look, I just don’t believe it.
Here’s my question: Is it working?
My vote: it’s not. Here’s the evidence.
Business intelligence (BI) is greater than a $50 billion market, yet usage of BI tools hovers at under 30 percent. What does this mean? That means seven out of ten people are uninformed. Let’s play out a scenario: I’m having a party, and I invite 100 people. Thirty of them get an invite sent directly to them, and 70 do not. How many people make it to my party? Less than 30 percent. We wouldn’t skip out on informing 70 percent of our guests about a party’s start time and location, so why would we find it acceptable that 70 percent of our company has no clue what’s going on with the business?
Some may say: “Well, the tools aren’t the issue, Stef.”
To that, I would respond, “Listen up, buttercup, I know the issue is much bigger than just the tools themselves. But the tools have created a full-blown human capital crisis!”
Data science is one of the fastest-growing careers in the U.S. As the demand for people in these jobs is accelerating and growing at an exponential rate, the supply is simply not keeping up. Yet, as in-demand as people in these jobs are, according to this Harvard Business Review (HBR) article from January 2019, one of the biggest gripes about today’s data scientists is that they do not have the skills to communicate insights to stakeholders.
Executives, meanwhile, complain about how much money they invest in data science operations that don’t provide the guidance they hoped for. They don’t see tangible results because the results aren’t communicated in their language.
So now, we have issues with the tools and misalignment of the people’s skills who primarily use the tools. Really smart people, and publications like HBR, are saying things like, “Well, you should be formulating your data science team’s strategy to literally hire people who have certain skills.” This essentially suggests that if you can’t find a unicorn data scientist who has it all—one who gets the data AND gets the people—you should build an entire team of people in the data science profession and have unique single skills. For example, a data scientist who also specializes in project management, a data scientist who also has subject matter expertise, or a data scientist who also specializes in storytelling.
My issues with this strategy?
- Good luck hiring and retaining this team of in-demand professionals.
- Why spend all this money solving for a tool issue that creates a human capital issue?
- Why, in 2019, don’t we expect tools to do all of the above for us?
We need to leverage our data to tell us stories that we can read and understand.
What I needed, when I needed it
So, here I am, seeing red after watching yet another data storytelling video that isn’t talking about actual data storytelling and then reading the HBR article, when something magical happened. This video from A16Z dropped in my lap. Like a gift sent from Heaven!
Andreessen Horowitz’s Enterprise Deal Partner, Jad Naous, talks with Operating Partner, Frank Chen, about something that ACTUALLY made sense to me: the future of decision-making. Existing tools aren’t working (check), and we shouldn’t depend on people to fit the tools (double-check). Instead, tools will meet the people where they are, supporting the needs of the 90 percent who are unsupported by today’s tools. These ‘new tools’ are designed for “operational intelligence.”
Finally, someone who gets me
What are the requirements of these tools to make your operation more intelligent you may wonder? Well, here’s what Naous suggests:
- Continuous. “They can’t be eventual like BI. Your questions have to be answered in the moment. No going back to the data for a few weeks and then bringing back an answer.”
- Immediate. “They have to be real-time. They can’t be on a batch basis. They have to deliver information on what is happening right now.”
- Self-service. “You can’t have someone else doing all the work for you. The tools have to give you insights that are catered to you.”
Mad respect, Naous. Thank you for telling the world that we should expect more and expect different. Additive to what you’ve laid out, I would actually push you to go one step further. I propose putting a stake in the ground and saying there is a fourth requirement. That is, these new tools to be:
4. Stories. They must communicate with you with language. You should expect these tools to speak to you the way that humans do: in plain English! And not only be natural but also concise, impactful, memorable, and consistent—just like a story.
Immediate, continuous, self-service, STORIES
People at Narrative Science will tell you I’m a pretty “passionate” individual. I tend to get wound up about things that matter to me, both good and bad. I wrote this because I needed to get this off my chest.
I came to Narrative Science four years ago because I was done with the confusion. I am done with the misrepresentation. When I heard there was a company in Chicago that was delivering on the promise of making operations more intelligent by delivering data storytelling tools, I had to be part of it. Our product actually tells stories with data by turning it into language that literally anyone can read and understand.
That’s why we created Lexio. And it meets all of Naous’ requirements.
Immediate. It connects to your Salesforce data, pulling it directly into the tool, analyzing it, and writing stories about it that answer business questions. For example: How many deals did we close, and what were our bookings? What was our average deal size? How did our number of deals and average deal size change relative to the previous period? How did we perform relative to our goal? Who were our top performers?
Continuous. With the direct connection between Salesforce and Lexio, your stories are updating constantly, so if your business is moving as fast as ours and you want to see how your pipeline changed from the beginning of the day at 9 a.m. to the end of the day at 5 p.m., Lexio is ready to go when you are.
Self-Service. If you are the CEO and you want to get a business update on Sunday, you shouldn’t feel guilty about reaching out to your analyst over the weekend and disrupting their day at the beach. Your company is your life, and you should be able to get analyst quality updates whenever, wherever you want.
Stories. Let’s be real. It’s almost 2020, and Excel, charts, and graphs are so early 2000s. Anyone, including my grandma, can read and listen to a story.
Look, the future is here. It’s just not evenly distributed yet. Operational intelligence for your entire workforce is here. Data storytelling (the REAL data storytelling) is here. At Narrative Science, we are writing the future, and we are looking for partners to co-author it with us. Join us. I promise you will never think about data storytelling the same again.
P.S. Do I actually believe data experts are trying to misrepresent us? Definitely not.
I believe people who know data AND can communicate effectively (including those at HBR) are optimists. Everyone is trying to figure out a way to make the most out of the tools that exist today. I used to do that too, but now there is a better way. I believe that when anyone sees our product, they will understand what data storytelling really is. Give us a call. We can’t wait to show you Lexio!