Data-Driven Work Cultures: Bryan Smith Of ThinkData Works On How To Effectively Leverage Data To Take Your Company To The Next Level
An Interview With Fotis Georgiadis
Make your data accessible: Once data is found, people need to be able to leverage it to scale projects or whatever they’re working on.
The proper use of Data — data about team performance, data about customers, or data about the competition, can be a sort of force multiplier. It has the potential to dramatically help a business to scale. But sadly, many businesses have data but don’t know how to properly leverage it. What exactly is useful data? How can you properly utilize data? How can data help a business grow? To address this, we are talking to business leaders who can share stories from their experience about “How To Effectively Leverage Data To Take Your Company To The Next Level”. As part of this series, we had the pleasure of interviewing Bryan Smith.
Bryan Smith is the Co-Founder and CEO of ThinkData Works Inc., a Toronto-based technology company whose platform is used by some of the world’s largest organizations to process and refine data into usable products. Prior to founding ThinkData, Bryan worked for the Canadian Government as a Sr. Policy Advisor to the President of the Treasury Board of Canada. In this role he helped implement the Government’s “Value for Money Ethic”, leading to over $7B in annual savings and the first transition from deficit to surplus in the past 20 years.
Thank you so much for joining us in this interview series. Before we dive in, our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?
Before I got into entrepreneurship, I got my start working for the Canadian Government as a Sr. Policy Advisor to the President of the Treasury Board of Canada. A highlight of my time there was helping implement the Government’s “Value for Money Ethic” initiative. I was really proud to support this project as it led to over $7B in annual savings and the first transition from deficit to surplus in the past 20 years.
Working in the government for several years, I became well-acquainted with how much data is publicly available, but I was also made aware of the challenge for organizations to access and put it to use. I made the jump to entrepreneurship because I wanted to create a conduit between the people making data available and the people wanting access to it. My co-founder and I recognized the value in data that organizations struggle to unlock to its full potential due to the barrier of the tedious, time-consuming task of cleaning and organizing data — otherwise known as data cataloging and data enrichment. ThinkData Works was founded to take care of these two steps so that data scientists can access data in a more automated way at scale, enabling them to focus more time on data science work.
Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lessons or ‘take aways’ you learned from that?
When we first started ThinkData Works, we were bootstrapped and had to be extremely frugal. We ‘incubated’ our company in a shared space with many other companies that saw a lot of turn over (both failed ideas and companies graduating to “the next level”). In those early days, to keep operating expenses as low as possible, we used to have to cut all types of funny deals with other founders to trade them for desks, chairs, monitors, whiteboards, etc. In fact, one time we battled out a large portion of desks in a high stakes game of Super Smash Bros!
As your company grows and you accumulate more money, through revenue or fundraising, leaders tend to become less cautious and intentional with their spending. Sometimes I find companies who skipped the early-stage phase of bootstrapping find it harder than others to control costs and spend — especially as we go through the tech correction environment we’re currently facing. I’m not saying the lesson here is to gamble on Nintendo games, but remembering that we used to always find a way to make ends meet when we had nothing has given us the foresight now to have faith when navigating through difficult times — where there is a will there is always a way!
Is there a particular book, podcast, or film that made a significant impact on you? Can you share a story or explain why it resonated with you so much?
Two books come to my mind. First is ‘Good to Great’ by Jim Collins — we built ThinkData Works around the hedgehog principle developed in the book. The key learning is that focusing on how you can be the best in the world at something is what separates good companies from great ones. I really resonated with this idea and try to always think beyond what our team is just good at, to what we can be the best at in the world.
Another impactful book that is especially timely given the economic times we’re in, is ‘The Hard Thing About Hard Things’ by Ben Horowitz. As a founder, you encounter countless tough decisions and this book does a great job exploring how to navigate the diverse challenges of building a company.
Are you working on any new, exciting projects now? How do you think that might help people?
In terms of new and exciting projects, we recently announced our partnership with Dun & Bradstreet to help financial institutions improve their anti-money laundering (AML) programs with our data enrichment solution. We also recently launched our data catalog and enrichment services on Google Cloud Marketplace, to provide enterprise customers with reduced time-to-value and access to Google Cloud’s leading AI and data analytics capabilities. The partnership builds on a growing ecosystem of data and management tools available to customers of both organizations.
When it comes to directly helping people, I’m really proud of our Supply Chain Resiliency Platform (SCRP) in partnership with Palantir Technologies Canada, a leading software company specializing in big data analytics, and Martinrea International, one of the leading Tier One automotive suppliers of vehicle parts, assemblies, and modules. They successfully built and deployed an SCRP powered by trade data from multiple global sources that gives manufacturers and logistics companies deep insight that goes beyond their direct supply chain. This innovative solution is backed by the Government of Canada and the NGen supercluster, an industry-led not-for-profit organization that leads Canada’s Advanced Manufacturing Supercluster, whose mandate is to help build world-leading advanced manufacturing capabilities in Canada for the benefit of Canadians.
As the current global supply chain crisis will continue to negatively impact commerce in 2023 and beyond, the need for an innovative solution that safeguards manufacturers against risks and disruptions is becoming increasingly necessary, and I’m proud ThinkData Works is working to be part of that solution.
Thank you for all that. Let’s now turn to the main focus of our discussion about empowering organizations to be more “data-driven.” For the benefit of our readers, can you help explain what exactly it means to be data-driven? On a practical level, what does it look like to use data to make decisions?
Many organizations think of data as a physical asset that sits on a shelf. To be data-driven is to actively collect and use data to drive decisions. Consider this — a building full of books isn’t a library, it only becomes a library when a system exists that enables users to access, share and discover information. In the same way, organizations can only become data-driven once a system exists that enables users to access, share, and discover the data.
Making data-driven decisions looks like drawing conclusions from data insights — whether owned or external — and then using these conclusions to inform organizational decisions. For example, a coffee shop could look at data around weather patterns in the country from where they import their coffee beans from to foresee delays in their supply chain. If a drought is incoming, they can proactively seek out suppliers in a different region to avoid running out of coffee at their shop.
Which companies can most benefit from tools that empower data collaboration?
Being data-driven is sector agnostic. Taking the steps to become a data-driven company today is important to ensure the business will be around tomorrow, as data will become a core aspect of decision making for any company that wants to make it in the 21st century.
We’d love to hear about your experiences using data to drive decisions. In your experience, how has data analytics and data collaboration helped improve operations, processes, and customer experiences? We’d love to hear some stories if possible.
An interesting and perhaps unexpected way our data enrichment has supported organizations is with stamping out illegal activity through anti-money laundering (AML) efforts. Scotiabank was one of the first organizations to use our data enrichment portfolio to identify patterns in global trade to improve the outcomes of their AML programs.
Fighting global organized crime with data enrichment solutions is just one example of the power of modern data science to achieve not only business objectives, but also advance environmental, social, and governance (ESG) initiatives. Other applications we’ve seen include manufacturing firms using our data enrichment and cataloging services to optimize their supply chain through crises, as well as federal governments developing data-driven policy based on pulling together assets and making decisions with hard data.
Has the shift towards becoming more data-driven been challenging for some teams or organizations from your vantage point? What are the challenges? How can organizations solve these challenges?
Yes of course, with any change there is always friction and growing pains. Historically, organizations have looked at data requirements as a storage and security problem first and as an access and discoverability problem second. This creates friction between data stewards who are owners and protectors of data and data practitioners who put data into use.
The reason data cataloging is so important is because the big challenge for organizations to overcome with their data strategy is to introduce proper governance that does not inhibit discoverability and usability. This requires continuous data cataloging as businesses transition to become data-driven.
Ok. Thank you. Here is the primary question of our discussion. Based on your experience and success, what are “Five Ways a Company Can Effectively Leverage Data to Take It To The Next Level”? Please share a story or an example for each.
First and foremost, to effectively leverage data to take it to the next level in an organization, you need to start with a strong data strategy. To develop a strong data strategy, I would break it down into the FAIR principles of data (findable, accessible, interoperable and reusable):
- Make your data findable: In order to use data, it has to be discoverable across organizations.
- Make your data accessible: Once data is found, people need to be able to leverage it to scale projects or whatever they’re working on.
- Make your data interoperable: Data needs to be able to be used across multiple functions — it needs to be standardized as opposed to siloed.
- Make your data reusable: As you don’t want to build from the ground up every time, you have to be able to reuse assets to get the most value out of them.
These principles are why data cataloging is one the fastest growing industries from a Technology Acceptance Model (TAM) perspective.
The name of this series is “Data-Driven Work Cultures”. Changing a culture is hard. What would you suggest is needed to change a work culture to become more Data Driven?
I think the first step is changing the focus of the work culture. The mistake most organizations make is focusing on the storage and security of data from the get-go — while this is important, the data is useless to your team unless it’s accessible and discoverable. Once you establish a culture and system where those who can benefit from the data can easily find and access it, then you can focus on the data’s storage and security.
This kind of cultural shift is admittedly difficult, as data is ultimately the crown jewel of many organizations and how you handle it should not be taken lightly. Instead of doing a complete 180 cultural shift, my suggestion is to find ways to start implementing a transition towards openness and discoverability, and leverage positive results from this shift into a larger culture change.
The future of work has recently become very fluid. Based on your experience, how do you think the needs for data will evolve and change over the next five years?
At the end of the day, data needs to be discoverable and accessible. Data is like a vascular system, it needs to flow to various parts of organization to be used; it can’t be segregated or walled off. As data science becomes an integral part of all organizations, it will be increasingly important to incorporate data enrichment and data management systems into every aspect of a business.
How can our readers further follow your work?
You can keep up-to-date with what I’m working on by following me on LinkedIn.
You can also learn more about ThinkData Works at our website, https://www.thinkdataworks.com/, and follow us on Instagram,, Twitter, and Linkedin.
Thank you so much for sharing these important insights. We wish you continued success and good health!
Data-Driven Work Cultures: Bryan Smith Of ThinkData Works On How To Effectively Leverage Data To… was originally published in Authority Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.
