Hello, my name is Derek Doel and I’ve been in the Data Science discipline for the last decade. In that time I’ve seen small businesses and enterprises alike change their perspective on the value that data has for their company. It is no longer about ‘why’ your business should focus on data as a product, but on the ‘how to’ for integrating data as a product within your company. As a leader concerned about delivering success on data projects, it is now left up to you to define how data initiatives are executed in the whirlwind of all other business objectives.
While playing a leadership role in data utilization, I’ve had some wins among the losses that have helped build data product strategy for the events industry. Our company objective was to mature the events industry in their data strategy by giving them data products to visualize the operations of event management (dashboards, charts, and self-serve reporting), and offer customization on those data products. To meet the SAAS roadmap deliverables, we had to adapt our product development strategy. Here are the three organizational initiatives we found most successful in accelerating data product development.
The complexity of our customer’s data made it difficult to create scalable data products without first putting an emphasis on democratization. We gave our customers access to all their data by creating report builders, dashboard builders, and visualization builders. All as part of the software and scalable across our entire customer base. At our company, the product team is so passionate about data that they named themselves DataTron.
This team is made up of a product manager, a UX designer, a QA engineer, front-end developers, and back-end developers. Their key focus is making it easier for customers to self-serve their data usage and business intelligence on top of the data they’re creating
Data is not localized to just a single product team. If you think about it, every product is designed to produce data. Thus, it seems that every agile scrum team has a need for thought leadership and design around their data products. Rather than turn those data needs over to a single downstream team, we embedded data scientists within each software team. This kept the ownership of the solution on the team that produced the data. It also allowed data scientists the flexibility to research cross-product problems (like machine learning) in a centralized team.
This team is a lightweight product discipline. Each data scientist is responsible for the utilization of data within their product domain. A data scientist can function on multiple product teams, and all data science work is prioritized across the entire product strategy. This has ensured our company is focusing on the most import data initiatives, simultaneously keeping product managers focused on other deliverables.
The data products are ready and available to use, and the customers will line up to take advantage of your software because of them, but their success is dependent on their own data literacy. SAAS business intelligence is matching customer’s data needs into a product journey that facilitates clean data collection and readable intelligence. The importance of defining what products will be used before the data starts to trickle in is critical. A BI discipline acts as a steward and tutor for their customers utilization of data products.
This discipline provides valuable feedback to data scientists and the data product team on what problems our customers are facing. They’re also the quickest to adopt the utilization of data products.
Business leaders looking to rethink how data products get built and serviced for your company, I hope my odyssey has given you clarity. My goal is to provide you with a blueprint for implementing a successful data strategy. This will be some of the most exciting times your company will ever voyage on!
If you need support/guidance, and want to avoid some of the pitfalls that come with complex strategic data initiatives, connect with us on our slack community.
You can also hear the analytical odyssey of others in the SAAS data product community on The AO Podcast
