Many people I speak to in our field tell me that storytelling is the last mile problem in people analytics. If you don't tell the story in a compelling way that resonates with your audience, then it is highly likely that no action will be taken. That means all your hard work in collecting, cleaning, and analysing data will be a waste of time.

My guest today is Cole Nussbaumer Knaflic. Cole honed her skills in Google's fabled people analytics team and now helps people and organisations become better at storytelling with data, making sense of data, and weaving them into compelling stories that drive action.

You can listen below or by visiting the podcast website here.

In our conversation Cole and I discuss:

• Why good storytelling is so important when it comes to data visualisation

• Three tips to improve your storytelling with data skills

• How to adapt your story depending on the audience

• Whether AI and Automation is a threat or an opportunity for HR

This episode is a must listen for anyone in a workforce or people analytics role, HR business partners and indeed any HR or business professional who has to communicate data as part of their role.

Support for this podcast is brought to you by Crunchr. To learn more, visit https://www.crunchrapps.com.

Interview Transcript

David Green: Today I am delighted to welcome Cole Nussbaumer Knaflic, CEO and founder of storytelling with data to The Digital HR Leaders Podcast. Welcome to the show Cole.

Cole Nussbaumer Knaflic: Thanks for having me here, David.

David Green: It is great to have you here, fresh off the plane.

Cole Nussbaumer Knaflic: Yes I got in at five o'clock this morning from the states.

David Green: We will keep you alive with some testing questions.

So welcome to the show can you provide listeners with a quick introduction to your background and what you are doing currently?

Cole Nussbaumer Knaflic: Sure. So my name is Cole and I am CEO at Storytelling with Data where our goal is to try to help people make graphs that make sense and weave those into action inspiring stories.

So probably the part of my background that is going to be most relevant for your listeners is the time that I spent on the people analytics team at Google. So I joined Google back in 2007 which was right as we were starting to centralise analytics within people operations. Prasad Setty had been brought in a couple of months before I started. The analytics folks had previously been a couple of analysts in compensation, a couple of analysts in benefits so they thought let's get them all together and increase the power of that group. So when I joined, this was back in 2007 the team was tiny, which was great because I got to touch all sorts of different things and it was a super exciting time to be part of Google people analytics because everything we looked at, we were looking at for the first time. And so we did studies on what makes a manager effective. How do you actually measure that or quantify it? Hold people accountable to it? What drives when someone is likely to leave the organisation? How do you predict who is going to leave? What sort of interventions can you test out to change those behaviours? Also the opportunity while at Google to develop a course on data visualisation and travel to our offices around the world, teaching people how to make good graphs. One of the things that stood out to me in doing that was I would be in these classes where there would be salespeople and engineers sitting side by side.

People with totally different skill sets, different backgrounds, different reasons for wanting to be communicating with data. I came to realise that the skills that are useful in this space are not specific to a given role or industry, rather these are skills that pretty much anyone can use to have greater impact in their day to day work life.

So back in 2013 I left Google to start Storytelling with Data and we spend most of our time teaching workshops where we will go into organisations and spend half a day or a day with a team really getting into how they communicate with data and using that to teach really straightforward lessons that everyone can use to improve how they communicate with data.

David Green: Perfect. Why is good storytelling so important when it comes to graphs, data visualisation and communications?

Cole Nussbaumer Knaflic: If you can not tell a story with that data you are not going to be able to get an action, the action that you need. I think there is a tendency, particularly for highly technical folks or folks who come up from a technical background, to want to just put all the data out there but that is a challenge, right? Because we are assuming our audience knows the context well enough that they can figure out what is important. We are assuming they are going to take the time to do that and so a lot of great work actually gets lost because we do not take the time to put the words around it to make it make sense, to focus attention where we want people to look and do these things so that the ideas that we have in our head actually come across to the person on the other end.

David Green: Yes I have heard it described as the last mile problem in people analytics, presumably any type of analytics actually, and it is something that so many organisations and people analytics teams seem to overlook.

Even if you are working on the right business problem, you can do some great analysis and generate some fantastic insights but, as you said, when it comes to then actually getting action taken the message gets lost in a myriad of different graphs and charts. Which actually can be quite hard for people to understand if they are not technical themselves.

Cole Nussbaumer Knaflic: Yeah. That is one of the things that we lose sight of because anytime we are working with data, we are working on our project, we make a graph, we know exactly what that graph means because we are the ones who made it, but it means we actually have a lot of tacit knowledge in our heads that we have to put out there for others to be able to use.

So we can do things like use colour sparingly to direct our audience's attention to where we want them to look, put words around our data, not only to make it clear what our audience is looking at but what do we want them to take away from it. Put that takeaway into words.

David Green: Let's go back to your time at Google. Obviously Google, which is rightly seen as one of the pioneers in people analytics, it was not the only organisation doing it but I think it was the first organisation that started to openly share some of the work that it was doing and some of the projects that you referred to. I think it is probably fair to say that when you started there back in 2007 that HR was not really renowned for being data driven, probably even in Google. So when you came to put that visualisation course together how did you help your HR colleagues first to improve their data storytelling skills?

Cole Nussbaumer Knaflic: I think the biggest thing that we did was forming partnerships between the analytics team and the folks on the analytics team and the HR business partners. Because what we found early on was when we tried to work in our bubble and come up with what we thought were fantastic, brilliant things and push them on to the HR folks who then would work with their partners, that did not work so well. Oftentimes it was because there was context that was really important to know and that is what the HRBP’s, the business partners bring to it. So over time we developed a model where we had points of contact, working with each of the areas of business and their HR folks. I actually played that role for a number of years for the sales organisation and then later for YouTube where I sat as part of the HR team for that area, which meant I was able to understand what is going on in the business, what is happening, what programs the HR folks were driving for that part of the business. Get that context, be able to bring back to the analytics team and then also be able to take some of the research and projects that the analytics team is working on to the business where it would make sense and when it would make sense. So we moved away from any sort of blanket everybody gets everything, to figuring out how do we partner and do strategic things in the right areas where there is going to be reception for it and where it is going to make sense given the other priorities of the business and the HR team.

David Green: So you played the role, which has been called today, a translator role. It is taking some of those business challenges and questions and helping the team to convert those into analytical projects that they could work on. And then the same thing, taking some of the insights from those analytical projects out and helping the business understand them and then take action on them.

Cole Nussbaumer Knaflic: Exactly and that translator role is one that I have found my way into everywhere that I have been. I think it has been a combination of my background, scholastically is applied mathematics and business, and so I can speak both languages and help translate for each other and help people figure out what are smart questions to be asking if something does not feel right and to help the technical folks with the communication pieces that sometimes get overlooked.

I had a colleague, a friend of mine who we shared an office for a number of years. Brilliant guy. PhD. Smart, which meant he had a hard time speaking plain English to people. So we would sit and say okay, tell me what you are trying to get across? Okay say it in fewer syllables. Say it in fewer syllables, right?

Take that word out. What other word could you use? And that is all part of that translation, it is not about dumbing anything down, but it is about thinking about who your audience is and how you can speak in ways that are going to be accessible, easy and not make people work harder than they need to.

Making data visual is another way to do that because when we can take data and we can make it something that other people can see, it allows us to explain it in better ways and really inform in ways that when it is just the data becomes difficult. So that is part of the power of turning numbers into pictures.

David Green: So Cole, if you have to just give three tips to listeners on how to improve their storytelling with data skills, what would they be?

Cole Nussbaumer Knaflic: So my first would be to be really specific about who your audience is and design everything you are doing with that audience in mind. I think too often we design a communication, write a PowerPoint deck for ourselves, for our data, for our project, it is really easy to do.

It is actually a much harder but more effective thing to step out of ourselves and think about how do we design this first and foremost for our audience? Which means thinking about things like who are they? What do they care about? What keeps them up at night? Because if we can frame what we need our audience to know or to do in terms of those motivating factors, then we get their attention and can get our message across.

So I think first would be audience.

Second and I mentioned this earlier, would be think about where you want your audience to look and create sparing contrast to achieve that. The easiest way to do that is sparing use of colour and if we think about not designing anything to be colourful but rather working in grey scale and then using colour really intentionally as a cue to our audience, it tells them where they are meant to look. That can be really effective for quickly getting our audience to the point that we are trying to make.

Then thirdly would be words, use words. I think sometimes when people think of data visualisation, they think it should all be numbers and pictures and that words have no place but words play a very important role in making those numbers and pictures understandable for our audience. So that means we need to title, every access should have a title. If there is a key takeaway, which if you are at the point of explaining something there should be, put that down in words.

If we do those three things, we think about our audience, we designe with them in mind, we use colour sparingly to focus attention and words that tell our audience why we want them to look there and what the takeaway is. That is a successful scenario for communicating effectively with data.

David Green: Perfect. Well, I was fortunate to attend one of your workshops a couple of years ago and I do remember the tips around colour and I have actually taken that forward since. I do seem to get more speaking gigs, so maybe I owe you some commission or something.

One of the other things that really struck me during the masterclass that you ran was around the narrative arc that you took from classic storytelling and how you applied it to presenting data. I think that would be something our listeners would really enjoy hearing about.

Cole Nussbaumer Knaflic: Sure thing, so if we think of a story, stories typically follow this narrative arc where you start out, there is a plot. Tension is introduced, that tension builds in the form of a rising action. It reaches a point of climax. There is a falling action, a resolution. Turns out we are hard wired to remember stories that come at us in that form.

The challenge is the typical business presentation does not look anything like that. Typical business presentation follows a linear path where maybe we start off with the question. What did we set out to solve for in the first place? Then the data. Where did we get it? What did we do to it? What assumptions did we make?

Then the analysis. What were the actual statistical methodologies we employed? Then finally our findings or recommendations. This is the typical path of a business presentation and that is because this is the path that comes most naturally because it is the path we typically go through when we are analysing data. But it is a very selfish path because at no point along that typical linear path do I have to give any thought to my audience.

For me that is the biggest shift that happens when we think about our business communications not along the linear path, but reframing them making use of this narrative arc.

To have an arc you have to have tension and it is not about making up tension, if there is no tension you would have nothing to communicate about in the first place. Also it is not the tension that matters to you, it is coming back to audience, It is the tension that matters to them. If you can identify that, you can get their attention, build credibility and drive them to the action you need. So we teach the narrative arc, we teach it in our workshops, both books go into this as a framework to be able to use as another way to think about how you might communicate data-driven findings.

David Green: So leading onto the next question quite nicely. How have you adapted your story to the audience and then If you have got a people analytics case, for example, you might be presenting that to different audiences at different times, which might mean you need to find a different tension, presumably?

Cole Nussbaumer Knaflic: Yes, and that is exactly right because too often what we do is we craft a single communication that is meant to meet the needs of many different audiences and the challenge when we do that is we actually don't meet any of those needs as clearly as we could if we just divided it into multiple things. That does not mean we completely rework things every time but it means when the stakes are high then we want to be specific about who the audience is and how we can cater to them specifically.

So, yeah, it means the tension will change as you have different audiences for your data stories.

David Green: Presumably you will do your homework about your audience and understand their technical appreciation, that is not the right word, but their technical knowledge for example.

Cole Nussbaumer Knaflic: Exactly finding out how they want the information, what level of detail they need, what questions they are likely to have.

The more fact-finding you can do about your audience the better. If that is not possible or if you are feeling not prepared in that area, have a colleague play devil's advocate or play a really tough audience member. Oftentimes talking through things, getting clear on what assumptions you are making, how big of a deal it is if those assumptions are wrong, and playing through those roles can help make the case more strongly.

David Green: Also that implies that you need to take a little bit more time over putting your presentation and visualisations together. It is funny, isn't it? We spend a lot of time finding the right business questions to work on.

We spend a hell of a lot of time doing the actual analytics, but this probably leads on to the next question, a common mistake is that people do not spend enough time on actually communicating those results.

Cole Nussbaumer Knaflic: Which is interesting to me and I think it is the piece that gets skipped, or it gets the least amount of time devoted to it because you can not skip the other pieces.

You have to figure out what the question is you are trying to solve for in the first place. You have to go gather the data and do all of that. But after you do all of that you can just throw it in a graph and call it done, but that graph or the communication, that is the only part of everything that your audience ever sees. Whether they should or not, it has connotation on the level of attention to detail you spent on the rest of it and that is the point where your work is either going to succeed or fail. So it deserves at least as much time and attention as those other parts of the process. The more time and attention you can spend there and be thoughtful about how you design your graphs, be thoughtful about how you weave that into a narrative, the more success you will have in getting your point across and actually driving action based on the data, which is what we want.

There is this tendency to just want to put the data out there, but that is a dangerous thing to do because audiences are faced everyday with a ton of data. So when we give them more data, it is really easy for them to say, oh, that is interesting and then move on to something else. Or worse, they ask you for even more data and you have this death by data cycle. Whereas if we take it to the next step, we say not only audience here is the data, but here is something you should do with this data. Here is an action to take or a discussion to have or some options to consider. Now your audience has to respond to that and even if they disagree, it starts a conversation and it is a conversation focused on the right sort of things. It is a conversation that often gets missed when we stop at the step of simply showing data. So it is always thinking it through full course of not only what do we want to inform our audience of, but what do we want them to do now with that new information. The more thoughtful we can be about this, the better position we put ourselves in for success.

David Green: You talked about the rising tension, that suggests that actually don't be afraid to build some emotion, make people feel they have got to do something to sort this out.

Cole Nussbaumer Knaflic: To the extent that is appropriate, given the scenario, given your audience. If we had gone in front of the engineering team with a highly emotional story, that probably would not have worked so well. With the engineering team we had to go in with the facts and the statistics and the methodology and we actually had to take them through that linear path, that I talked about earlier, so that they can be bought in. Actually we had to do more than that, we would have to get them involved in our study design so that we would have advocates once we got to the output. But yes, for a different audience, it will call for something different and so being cognisant of that and designing with that in mind.

David Green: So what are some of the other common mistakes you see around data visualisation and storytelling? We have talked about colour and we have talked about not recognising the audience.

Cole Nussbaumer Knaflic: I think one mistake I see, or one trap I see people fall into is to try to show something in a new novel way. What happens is oftentimes maybe it grabs our attention, but makes the actual data harder to get at. There is a reason that line charts and bar charts are common it is because they are actually really easy for us to read and most people have encountered them before, which means you face less of a learning curve with your audience for getting the information across. So I am a big believer in, for the majority of things, you are going to be looking at lines and bars. Every once in a while there might be a use case for something else, but most graphs out there have the perfect use case. The challenge is if we get too far away from that perfect use case and things get really tricky really quickly. We are actually going to be looking at an example in my workshop later this week that is from the HR realm. It is comparing reasons for leaving from exit surveys and the exit interview. It is fairly straight forward data but the original version of it is this bubble graph where they are different sizes and they are everywhere and they are different colours and it looks kind of cool. Somebody took a ton of time to put this together but you sit there and you grapple with what does the size mean? What does that mean? You spend so much time talking about the graph and trying to decipher what you are looking at that it is easy to not ever step back and think about what does the data say? What does it mean?

David Green: What are you trying to tell me?

Cole Nussbaumer Knaflic: Yes exactly and in this particular example we turn it into a simple bar chart and you can in a couple of seconds have a conversation about, hey, wait, this one reason for leaving is really high and it has suddenly become high. Why is this? What do we do about it?

What does it mean for the business? How do we turn it around? Now you have shifted the conversation entirely. We are no longer talking about the graph and grappling with what it means. We are talking about, what does this mean for how we run our business and how we should do that going forward?

Which is a really strategic shift to be able to make, and it is mostly by reaching for the tried and true sorts of graphs. So I would say that is another thing, do not go novel or crazy with your graphical form because you can or because that seems like a good idea.

David Green: I must admit you see it sometimes when people put it in bubble graphs, I think it is a great example, and they are all different colours which one am I supposed to be looking at first of all. What does it signify if it is over on the right hand side but it is small versus on the left hand side and big? So it can be quite confusing sometimes. If people are really nontechnical at all and they just want the insight then that confuses them and people switch off presumably as well. Then that is your audience gone.

Cole Nussbaumer Knaflic: That can actually be a good thing to do is anytime you are showing data, step back from the data and put what you want your audience to know into a sentence, saying it in a sentence. It is oftentimes if you can articulate that sentence, then you can iterate through different graphs to try to figure out which one is going to help me make that something my audience can see.

If you are struggling to come up with a sentence then you are not ready to communicate it yet.

David Green: You teach people how to tell stories all the time, but what is your favourite story and why?

Cole Nussbaumer Knaflic: Oh, that is an interesting question. So I do not know if it is my favourite, but a story that I use a lot during teaching is red riding hood.

I like red riding hood because there are versions of it that are told all around the world and everybody, for the most part, can remember it. So it is this fantastic evidence of the power of story and the power of repetition and how we can use those components when we are communicating with data as well.

So that is one of my go to’s.

David Green: There is definitely a rising tension in that story.

Cole Nussbaumer Knaflic: Yeah. Yes there is.

David Green: And then who do you learn from? So who have been people either you have worked with or people that you know or have seen out there that help you with the storytelling part?

Cole Nussbaumer Knaflic: This actually may be a surprising answer or an unexpected one to your question, but I learned a ton from my kids.

I have three little kids and the way they learn and put the puzzle pieces together of the world around them, I actually learn a ton from them when it comes to how do you teach others? And going back to some of the simple things, pen on paper and drawing or asking questions as a way to get to know the world.

The lead story that I did on our latest podcast, for Storytelling with Data, talks about this method of questioning to understand the world, that was inspired by them. So I spend a ton of time with my kids, which is probably part of it, but I learn a lot from them.

David Green: Yeah, I definitely learn a lot particularly in terms of how you have to break something down to explain it, which I guess is some of the stuff that we have been talking about.

Actually that has led me to another question.

Something else I remember about the masterclass you did was use pen and paper and post it notes to help build the story and you can swap things around then. I don't know if you want to talk about that a bit?

Cole Nussbaumer Knaflic: We still do that today. Some of my favourite tools are post it notes, little tiny sticky notes because when you are planning a presentation, you can brainstorm.

You can just get the ideas out of your head and out into the physical world and then you can start rearranging, moving things around, grouping things together, taking things out. Also if you can get feedback at this early stage, go to a manager or a stakeholder and say, Hey here is what I am thinking, it is rough, but is this generally the direction we want to go? Because if you can get the feedback at that point that says either yes that is spot on, execute or no, it is actually going this other direction. Now you have not wasted a ton of time and can be a nice way to get early buy in from others as well.

So I am a big proponent of low tech planning, post it notes, blank paper.

We also do an exercise with the big idea worksheet, which is just to get really clear and succinct on the message that you want to get across to your audience. I should mention that all of these exercises and much much more are included in my latest book, Storytelling with Data, Let's Practice.

David Green: Which we are definitely going to cover in a minute. I promise you on that.

Too many people, I am also guilty of doing it myself sometimes, you have got to do a presentation, and you start off going straight to PowerPoint and then you realise that it takes longer to do it on there.

Cole Nussbaumer Knaflic: It takes longer because oftentimes what we will do is we will start with some slides that are already there or we will take some time to make one and then you form this attachment, which becomes difficult.

So when you can plan in a low tech way it speeds up the whole rest of the process and keeps you out of this rut of trying to force things to fit because you have them or because you worked hard to create them and being thoughtful about the order that you take your audience through how the pieces fit together. It can be useful to doing a low tech way. It feels like it slows you down, but it actually speeds everything up.

David Green: Well we have talked about the new book. So your first book Storytelling with Data was published in 2015 and there is certainly a well thumbed copy sitting on my bookshelf at home very close to my desk.

You have recently released a follow up, Storytelling with Data Let's Practice. Which just has come out. When we spoke a couple of weeks ago, you explained that the book is constituted of three parts. Can you share that with listeners?

Cole Nussbaumer Knaflic: So practice is key for me. I mean, practice is how you get better at anything. But storytelling with data, practice is key for sure. So the new book is all exercises. It follows the same path as the original book but each chapter is divided into three sets of exercises. There is practice with Cole where I pose a scenario that you are meant to solve on your own. But then I also go through my solution as a way of giving a ton more examples and case studies and insight into the behind the scenes thought process.

Then the second exercise section within each chapter is practice on your own. So this is some of those sorts of canned exercises but without any prescribed solutions, which will be useful for the individual who just wants more practice, managers who want to assign exercises to their teams.

We have over a hundred universities around the world teaching from the first books as they are useful for university instructors.

Then the final exercise section is practice at work. You have done this in theory, you have done it with some canned examples. Now take a project you are facing in your day to day and let us break it apart and figure out when you should get feedback and how you should get feedback and who you should ask.

Let us set good goals around this stuff. There are exercises about creating a culture that is conducive to good storytelling and a whole host of other things. Each chapter ends with a series of discussion questions that can be fantastic in a group setting just to get people to continue to think and talk in the language of effective data storytelling.

So it is not a book that you sit and read. It is a hands on experience, like a workshop in a book, if you will, that if you take the time to go through all of these exercises you will be a master data storyteller.

David Green: Practice is so important because you can only learn certain amount from theory and storytelling is clearly a skill that you need to practice to get better at.

Cole Nussbaumer Knaflic: And something else that we have put together to help aid in practicing and skill development is the storytelling with data community. So as I have mentioned, I am a strong believer that to get good at this stuff means to practice and to get feedback. To talk with others who might be facing similar challenges or have come up with interesting solutions. Discover and be inspired by great work.

The storytelling with data community has been crafted to facilitate all of these things. It is an online community, it is free. The whole goal is to help support people around the world by improving the way that they communicate with data. So anyone can join over at community.storytellingwithdata.com.

Highly recommend that.

David Green: Well we will make sure that goes out in the collateral we put around the podcast so people can find it easily.

The future, what do you see as the future for Storytelling with Data. What impact will technology have?

Cole Nussbaumer Knaflic: There has been a strong focus on technical skills and programming skills recently, which are definitely important, but I think it has been a little bit at the expense of the other side of things.

There is tons of investment in data scientists, but those data scientists are going to be no good if they can't then communicate what they have done to someone else. So I think the next wave is going to be people who can make sense of technical analysis and translate that, coming back to this idea of the translator that we were talking about earlier, that those skills are going to be in hugely high demand.

So people who can hone those skills or are naturally inclined in that area are going to succeed.

David Green: Thinking about now, if you were to start a people analytics team in a company, you are head of people analytics, would you be looking to hire as many translators as data scientists?

Cole Nussbaumer Knaflic: Yes and I would be looking to develop the ability of the translation piece in the data scientists. Because I think it is a hard thing when you have people who are totally separate from the depth of analysis to do the communication. My view is the way it works the best is when you have got people in technical roles who then can also communicate, but certainly a mix of skills across people can help too.

David Green: And sometimes for the data scientists getting out into the business and actually meeting the customer, whether that is the employees or the actual end customer can actually help shape your work.

Cole Nussbaumer Knaflic: Absolutely. Anything that you can have that will help build context around what you are doing and the implications of it.

Absolutely.

David Green: Okay so that leads on to the question that we are asking all our guests on the show at the moment. AI and Automation do you see them as an opportunity or threat to HR? You can answer nuanced to your expertise and go beyond HR.

Cole Nussbaumer Knaflic: Opportunity for sure, that we should embrace or figure out how to harness it in to an opportunity, I should say.

I think specific to data visualisation and communicating with data in HR, what AI is going to allow us to do is, I do not think it is going to replace the brain anytime soon. That means people who know the context and are able to communicate and understand the depth of analysis, that is going to continue to be an important skill.

I think where AI is going to help us get faster and smarter is on serving up interesting things from the data so that we are able to find the stories faster and then we can spend more time, as we have talked about, on that communication piece to make sure that the important pieces of the data, that the important stories are coming across.

David Green: Perfect. I think certainly within HR there is a perception that all this technology means HR is either going to disappear or be shrunk considerably. I think that the actual storytelling skills and the softer skills probably become even more important.

Cole Nussbaumer Knaflic: Yes, I would agree.

David Green: We have talked about the book and we talked about the community. You have created a real movement behind what you are doing which i think is fantastic.

What are the ways that our listeners can keep in touch with you? You have talked about the community, but by all means, repeat that again.

Cole Nussbaumer Knaflic: I am active on Twitter, you can follow @storywithdata. We have a LinkedIn page for storytelling with data where we post things, daily articles, tips, tricks and that sort of thing. Our website for sure, it has a wealth of information that is storytellingwithdata.com and I definitely recommend signing up for and checking out everything that we have to offer at the community and that is community.storytellingwithdata.com.

David Green:  Perfect. Cole, It is a pleasure as always to speak to you. Thank you.

Cole Nussbaumer Knaflic:  Thank you David.