How to Build a Data Science Team — Interview with Jorge Lozano at Steelcase

Ben Newton
Feb 10 · 6 min read

In this episode of the Masters of Data podcast, I speak with Jorge Lozano, leader of the data science team at Steelcase. We discuss the application of data in the real world and how data science is adapting to the needs of the businesses it serves. Steelcase is a hundred-year-old company, the largest office furniture manufacturer in the world, and now a great example of a business utilizing data science.

Jorge first shares his background and where he started. He gained a bachelor’s degree in economics and started his career in business consulting, but decided he wanted a more quantitative role. In 2011, he became the Pricing Analyst at Steelcase. Jorge Lozano then shares what attracted him to data science and the compelling opportunities there. In this first formal role at Steelcase, he was part of some initial key breakthroughs in data science at Steelcase. He had an engaging leader and together they delved deeply into statistics and modeling. In 2013, he continued his education with a master's in actuarial science but was still drawn to return to Steelcase and to the discipline of data science.

I share my passion and nostalgia for the furniture industry (my grandfather worked for decades in the furniture industry in North Caroling), and Jorge discusses how the world of furniture manufacturing has changed and what it’s like working for a large furniture manufacturer today. Steelcase is based in Michigan with 1,300 employees around the world. He shares that Steelcase is an amazing employer and a second family to him. What stands out most about Steelcase for Jorge is not that it’s a large manufacturer, but that it is a business that unlocks human promise by creating great experiences wherever there is work. That means that they are not simply a supplier of office furniture, but a research-driven innovator.

Jorge continues by talking about why Steelcase cares about data science and its continuing investment in analytics. First, he states that embracing the digital age and technology is a necessity for businesses today. It is a matter of survival in the modern, hyper-competitive age of today. So, Steelcase’s main areas of investment in data science are first process improvement and internal data decision making, as well as driving product innovation and better customer experiences. In particular, Jorge explains the importance of workplace analytics. This area of analysis focuses on how space is being used and helping customers optimize a workplace based on improving workplace performance. Steelcase is working to collect this data and transform the data into actionable insights for their customers. Jorge wants to capture data based on “the user” using the furniture and “the chooser” that buys the furniture, in order to provide transformational experiences for both the type of consumers. With Steelcase’s industry reach and experience, Jorge thinks the company data science team could be leaders in this area.

Jorge continues by delving into the logistics and details of gathering data on client workspaces. One compelling example is to measure whether a space is occupied in order to measure the desirability of a space. From there he can deduce whether a space is used efficiently and if the client is achieving the correct work mode. Mapping office activities and work modes is an area of data science that truly excites Jorge.

Next Jorge describes what digital transformation looks like at an older company. He says it has been a journey for Steelcase to utilize data science. Since it is not a digitally native company, it was a challenge to determine a process for Steelcase. Jorge shares a few best practices for data scientists. First, make sure you know your customers and know what they need to improve their process. Jorge shares how you can partner with the subject matter experts to come up with compelling ideas that a data science team can’t do on their own. Second, if a company is new to data science, it is better to start with a simple, creative, achievable projects, rather than turning right away to complex problem solving and advanced methodologies. Third, he shares an example of forcing a solution to a problem and learning from his mistakes. Building a solution looking for a problem can waste the team's time and reduce the impact of data science on the organization.

Finally, when a business’s core work is not data science, like Steelcase, Jorge says it is important to always have a story to share so that non-experts can understand what his data science team brings to the table. To be able to successfully build momentum within an organization, he says you have to think carefully about how you communicate. Rather than merely talking about it, you can show it with a prototype for the organization to create a better connection and understanding. Jorge and I agree that showing an organization an outcome and a pathway to success creates a better connection than only discussing numbers and mathematical equations.

Now that Jorge and his data science team have success stories and have built strong connections, other Steelcase employees are starting to come to him for solutions and ideas. People are not just more aware of the promise of data science, but they also see real examples of how the data science team has partnered with the business and the I.T. teams.

Wrapping up, Jorge talks about what is next at Steelcase as the business is becoming increasingly aware of data science. Senior executives are pushing for his team to grow. The key focus right now is collecting data about end-users and how they utilize the product. Additionally, there are now opportunities for applying more complex models and sophisticated methodologies to deliver more and more value to the business. There is no doubt in Jorge’s mind that his team will play a critical role as Steelcase grows and changes for the better.


Outbound Links & Resources Mentioned

Takeaways

● Jorge, Data Scientist at Steelcase, started his career in business consulting, but moved toward a quantitative position and was part of some initial breakthroughs in the data science world.

● Steelcase’s goal is not just a manufacturer but a research based innovator.

● Steelcase’s areas of data science are process improvement and internal data decision making, as well as product innovation and customer experiences.

● Jorge’s goal is helping customers optimize a workplace based on workplace performance.

● Using data science, Jorge can decide if a space is used efficiently and is achieving the correct work mode.

● It is important to know your customer and know what they need to improve their process, because the solution may be something simple.

● A data science team should choose communication carefully, and not just tell but show and prototype for the organization to create a better connection and understanding.

● When there are strong connections and partnership with a data science team, the team is trusted with solutions and ideas for the company.

● The data science team will play a critical role as Steelcase grows and changes.

Newtonian Nuggets

Thoughts on what's going on in technology, data, analytics, culture and other nerdy topics

Ben Newton

Written by

Proud Father, Avid Reader, Musician, Host of the Masters of Data Podcast, Product Evangelist @Sumologic

Newtonian Nuggets

Thoughts on what's going on in technology, data, analytics, culture and other nerdy topics

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