HR Tech Expert Series: Managing Company Culture with Data— Bunch.ai

Quantifying culture. This term might seem obscure or even make you wonder, how can we measure such an intangible asset as company culture?

This question was probably asked many times by entrepreneurs, leaders and HR managers in the past. But only with the rising role of data, we are now closer to answering it properly.

Check all of our HR Tech Expert interviews from this series:

1. The Global HR Tech Ecosystem—with Enrique Rubio
2. How Businesses Transform Digitally—with Anna Ott
3. Tackling Global Challenges—with Philippa Penfold
4. The Role of Data in Employee Engagement—with Peakon
5. Creating Candidate-First Experience—with Hung Lee

A plethora of the latest HR tech apps is based on the use of data and AI mechanisms. Start-ups collect, analyze and utilize great deals of data to provide business leaders and HR managers with actionable insights. They use data to actually quantify soft aspects of business, e.g culture.

That’s what Bunch.ai is doing. Operating on the bleeding edge of HR tech, Bunch aims to not only measure, but also improve culture with their real-time tool analyzing team communication. The Berlin-based startup has recently raised $1.5 million seed round and plans to expand into the US market.

Its co-founders agreed to tell me more about operating in the data-based world, measuring culture and a never-ending dilemma of finding culture fit vs. achieving diversity in the workplace.

 

Charles Achmadzadech & Anthony Reo of Bunch.ai

Charles Ahmadzadeh running their engineering team and Anthony Reo leading the product team shared unique insights on compromising data-centric approach with a human touch.

See for yourself why the sentence: “If you can’t adapt to change, change will eventually defeat you” should be a motto of modern HR companies.

Joanna Staromiejska: What role does culture play in organizations and why did you decide to create a product dedicated to improving culture?

Charles Ahmadzadeh: Culture IS an organization. And organizations can’t exist without it.

Anthony Reo: The most cited definition of culture nowadays calls it the line between what you will accept and what you won’t. The question usually asked is “What would you fire someone for and keep someone for?”

It’s that behavioral yes or no.

Culture is more than just ping pong tables and keeping the office in a good mood. It’s about that behavioral red line.

That’s also why we decided to build a product dedicated to culture, because in the past, a lot of things related to culture were done based on intuition. So we wanted to conceptualize it somehow.

Measuring culture is extremely difficult. It’s done via gut feeling, intuition, and all that by a lot of managers. Managing it over time without the initial measurement is even more difficult.

We started with building one product, our assessment tool that measured two specific points in time, and we soon realized it was not enough. Companies need real-time, continuous measurements to always know what may and what may not be crossing that red line.

JS: How do you strike that balance between achieving diversity and finding culture fit in a company?

Charles: I think what's important, and that's one of the things that come from the research that Charles O'Reilly has been doing at Stanford for a very long time now, is that in order for diversity to work, there needs to be a common goal.

To create a diverse team you need to rally everything and everyone around a common goal or a common objective. It’s important to understand what is the one driving norm that can make everyone go in the same direction, and then be diverse in everything else.

I’ve heard a lot of people say that diversity failed them, “It’s not for us, it didn’t work for us.” This feels somewhat similar to people trying to do an Agile transformation without actually understanding the whole point of Agile. The process usually ends with them saying Agile doesn’t work. It’s the same with diversity. By trying to make everything diverse, people lose sight of the whole point. There’s no glue to keep them together.

JS: What to look for when hiring in order to get the best outcome?

Anthony: We need to acknowledge some bias here. In an early-stage company, the essence of who we are is kept within the small team—it comes from the founders.

We hire and set hiring “rules”, we feel the company’s culture the most. And I think it works similarly in other start-ups. Despite that possible bias, we are able to pick the best people among candidates. The people we consider our most successful hires, in terms of staying with us and performing the best, always demonstrate high adaptability and a growth-focused mindset.

Charles: Another trait that we look for in prospective team members is humility. Being able to understand where we fell and what our weaknesses are helps us get the best out of each other. It makes it easier to us for help and strengthen our team.

JS: How do you reduce hiring bias?

Charles: There are so many hiring biases, I don’t believe there’s only one. I tend to have gender hiring bias as 90% of my professional engineering network are white men. I use Emma, our Chrome extension that provides me with more gender diversity. So it’s a social network and industry bias.

Another example is how you interview candidates. If you ask different questions every time, it might give you unconscious bias against a candidate you don’t like for some reason, which may then lead to you asking questions the answers to which will never be satisfactory, no matter what. If you have a positive bias, you will ask questions and notice any positive answers.

It’s called the “promotion–prevention” effect. When you have a negative bias towards someone, you ask prevention questions, focusing on the negatives. When you have positive bias, you ask promotion questions, focusing on the positives. Asking what seems like the same question might produce completely different results. Look at “Why did you leave this company? Achieved everything and decided to look for new challenges?” compared to “Why did you leave this company? Looking for more stability?” Standardizing interview questions helps reduce bias a lot.

JS: We’re flooded with data we’re able to collect and analyze, which makes it hard to decide what to focus on. What should a company measure to at least try to quantify its culture?

Anthony: Quantifying culture is different than running an engagement survey per se. Any sort of quantified, data-driven approach to get a better, concrete sense of your workforce is good. We can’t say that an engagement survey is good or bad one way or another. If you want to quantify culture, rely on science-backed research. Go beyond just mood and engagement. Ask about everything you want to know even through Google Survey.

Charles: There are different levels of maturity, or rather fluency, in measuring culture. If you’re not doing anything, then you can start with surveys. But when you do indeed get started with surveys, by the time you get the results, your company is gonna be slightly different. You will get insights into the state of your company as it was two months ago. If you want actionable insights, you need a short-term feedback loop to measure culture and improve it. Some companies work with nudge or pulse surveys, which you send out more frequently. If it works, it’s perfect. If you fail to get enough responses, it’s better to invest in a real-time solution.

JS: What’s the role of data in an AI-based business like yours?

Charles: There’s definitely one thing to acknowledge and it applies to anything that’s AI-based or more or less based on data. Data is only quantitative. It can’t give you the qualitative aspect. It doesn’t give appropriate weight to certain aspects.

Let’s say you have representatives of minorities on staff. And if you only look at high-level quantitative data, you’re not gonna hear their voice. That’s basically a big problem. You need to keep it balanced. Talk to people one on one, do surveys, and add data on top of that. The role that data plays here is trying to check the bias that you have.

If you have a manager who’s very biased against gender, for example, then having data that can keep them in check, can help you debias their decisions or your own. When you combine both, you can have the best outcome. It’s the role that data plays, it helps you achieve a more accurate and objective picture of what you already have.

Anthony: Just to add some dimension to it, we should bring up what’s called the Holy Grail triangle in psychology.

When you measure culture, or anything else related to the mood or happiness, you have these three dimensions. The first is how you see yourself, the second how colleagues see you, and the third is how you actually behave.

If you have these three data points, you already have the most out of different methods or approaches. You have the most true sense of how you are without getting too philosophical. But we noticed that the market seems to be moving toward the “how you actually behave” aspect.

JS: How do you handle data management and data privacy in a data-based product? What would you advise to similar start-ups?

Anthony: Privacy plays a huge role in our data-based world. You’re getting someone’s actual behavior on record or measured. The process of collecting this data needs to be extremely clear because it concerns the “how you actually behave” context.

Charles: In the past 10-15 years, we’ve seen the biggest names in tech, like Facebook, making huge profits in advertising and increasing their value off the data they harvested. What’s happening now is that companies are beginning to realize that having all that data on people is more a liability than an asset. So when you switch your mindset, you start designing your business to make yourself the least liable. Instead of trying to collect as much data as you can, you try to limit the risk for your business. The less data you have, the better. You have to figure out what is the one thing you need your customers to have and discard everything else. I think GDPR is a good move in this direction. You can’t just keep data forever and for no reason. So my advice to start-ups would be to not fall into the trap of thinking that you’re an advertising company and to start seeing data as a liability for you and your users.

Anthony: Give your users as much control as you possibly can. I think it goes beyond just setting data privacy thresholds.

JS: At the event, Anthony said that “If you can’t adapt to change, change will eventually defeat you.” What are the biggest changes that HR departments should pay attention to right now?

Anthony: The one that came up during research and in product development feedback is the remote-first approach. A lot of customers come to us wanting real-time, continuous measurement of their culture because they’re remote-first. So the challenge for HR is to become acquainted with the remote-first culture and then establish new norms and new red lines. A lot of that happens digitally. How do we promote psychological safety in Slack or resolve conflicts online? It also brings the data question up again. A lot of remote first communication is not just done on Slack but also Zoom, video chat, audio, etc.

Charles: Catching up with what changes within your company is the biggest challenge. What worked when you were only ten people probably won’t when you’re a hundred people strong. Growth like that usually translates to a radical shift in dynamics, which often leads to founders losing much of their control over the culture.