On January 18th, we hosted our 2nd consecutive sold-out event, thanks to the Canucks Sports & Entertainment team and our panel of expert presenters. The Sportsbar Live! At Rogers Arena played host to 65 of some of Vancouver’s most driven young professionals.
We were fortunate to have a highly-esteemed panel from KPMG (Ozge Uncu), Hootsuite (Graham Gullans), TELUS (Jeremy Hopwood) and the Canucks (Andrew McNiece, Mark Niehe & Jonathan Wall), facilitated by Pollinate’s very own Tanja Gutmanis:
The lively panel discussion uncovered many thought-provoking insights into the world of Data & Analytics, and how it is being leveraged to drive unprecedented value for leading organizations and their customers.
1. Which one D&A use cases can you present where you have successfully driven action from insight?
Hockey Operations & Analytics:
D&A has come a long ways in the NHL over the years and teams who invest in their analytics department have a strong competitive advantage over the rest of the league. The role of analytic groups for NHL teams is to provide information in an easy-to-understand format so that players, coaches and executives can make the best informed decisions.
One of the main challenges in NHL’s analytics is data collection. Many data points are subjective; thus, expert judgement is key in order to ensure the data the team uses is accurate. All decision-making is built upon the data that is collected. Mistakes and poor judgement in this step can lead to major problems in the creation of a team; like poor trades, draft picks and player signings.
It is important to realize that D&A is only one part of the equation. During free agency, a team could find all the right analytics to decide which players they want to sign. However, if you’re located in a city like Vancouver with high tax rates, a high cost of living, and a lower population base than other cities, it may be more difficult to attract players.
Ozge provided an impressive example of KPMG’s Sports Schedule Optimization solution and how it was used to help the National Basketball Association (NBA) create its regular season schedule in a way that balanced player health, gate revenue and the fan experience. Using constraint satisfaction problem techniques, the schedule provided the following benefits:
- Improved “fairness” between each of the teams
- Increased rest for players between games (e.g. fewer back-to-backs)
- Reduced travel schedule and more efficient road trips (fewer total miles)
- Optimized television ratings (ensuring the best games are broadcasted at the right time and on the right networks)
- Maximized gate revenue
KPMG provided multiple schedules as options for the NBA with a single discrete “score” for each possible schedule, based on the organization’s own constraints to compare the overall quality of each schedule. Ultimately, D&A allowed the NBA to revolutionize its scheduling processes and is just one of many examples of its applications to the sporting world
Graham explained how Hootsuite uses data to drive revenue. The goal is to connect the dots between the data that clients have and measure how it can uncover insights to improve revenue. Hootsuite identifies clients who could further leverage social media to drive revenue for their business. We then take them through a value process where we showed them the value of social activities, relative to their business objectives. The goal was to find correlations in the social data and how it led to new customers. To add to Hootsuite’s dataset, we take a look at industry white papers to form assumptions and that was able to complete the loop to show that the business value tied to data.
2. The future of Data & Analytics
The tactical future of D&A will be the convergence of Artificial Intelligence, the Internet of Things, Augmented Reality/Virtual Reality, Big Data, and possibly even a future Human Intelligence. For a long time, data scientists have been trying to imitate the intelligence that exists in nature. Significant advancements have been made in this topic. For example we imitate how our kids learn - ‘reinforcement learning’, how ant colonies find the near-optimal solutions, how to make decisions under uncertainty, and even how we use our neural network as a model for training models. A compelling question to think about is - what if we can upload our learning power and use just processing power, instead of creating machines that try?
The future of D&A is using data to help customers with their own challenges and hypothesis. The big trend that caught on over the last 5 years has been data visualization, using programs such as Tableau, Power BI and Domo. Every major corporation now has a Data Visualization engine. Most big corporations also have data analysts and data science teams, but they don’t stretch across the organization. Therefore, most B2B organizations are looking for their vendors and domain experts to interpret data for them.
In the case of social media, you need a certain level of understanding of the data before working with it. Classically trained data scientists are not trained in social data, so customers turn to Hootsuite to interpret ita and help them with their performance. Hootsuite does not just provide a tool, but also provides deep domain expertise with each sale.
3. How to get more involved in Data & Analytics
“Get your hands dirty.” You cannot wait for a project to come to you, nor use lack of data as an excuse. People make their own decisions every day, so those who are truly interested in using D&A to improve their decision making can start with their own decisions. D&A is not just about developing machine-learning models; it is also about being curious, finding a worthy problem, and being creative and resourceful to overcome any barrier you might encounter. We are fortunate enough to live in the digital age and have unprecedented levels of publicly available data that is at your disposal.
Also, find like-minded people. There are regular hackathons and meet-ups that connect people who are interested in the same topics as you. There are many cost-effective analytics courses under $100, which can help you develop a foundational D&A skillset.
Not all universities offer analytics courses; however, statistics courses can serve as a valuable substitute to build a foundation for D&A. The best way to learn is by doing and experimenting with various datasets and analytics tools, such as Tableau. For those who are not currently enrolled in a post-secondary program, there are incredible resources online which focus on topics like data architecture. Online certifications are great and allow people to shift their resume to be data-oriented.