Stephanie Wagenaar, the problem-solver: Using AI-infused analytics to establish trust
This story is part of Analytics Heroes, a series of profiles on leaders transforming the future of business analytics.
Stephanie Wagenaar is a senior manager at BOLD, based in Baarn, the Netherlands. BOLD is a consultancy firm that supports businesses by combining strategies with their hands-on “analyze, advise, execute” approach, and offering “turnarounds, transformations, and transactions.” Stephanie focuses on the transformation aspect of this equation in their newest offering launching in autumn 2020: BOLD.digital. With this new venture, Stephanie continues to help businesses develop and implement more effective business strategies through the use of analytics, AI, and machine learning — with help from IBM Cognos Analytics and Watson Knowledge Catalog.
“Clients call me ‘Ms. Watson’,” laughs Stephanie. Her role as a consultant in data analytics is twofold: First, she’s delivering solutions — solving complex data issues and providing high-level strategy using Watson to clean data, build a business glossary, and utilize its AI capabilities. Secondly, she’s helping people in the organization understand how to be data-driven, and how to use the tools. Stephanie says, “It’s 50% technical, and 50% about people and relationships.”
Transformation built on trust
Stephanie keenly observes that it requires a considerable amount of trust for an organization to share its data with a consultant. Their data is the backbone of their organization, and it can be a sensitive topic. “Building a trusting relationship is the first step before you can excel together,” says Stephanie.
Stephanie uses Cognos Analytics and Watson Knowledge Catalog to help solve her clients’ biggest challenges. By utilizing both platforms, Stephanie establishes a level of trust with her customers and AI. Cognos uses AI for automating tedious, error-prone tasks, and guiding the user on the next analytical steps without them needing to know about the underlying algorithms. This auto-AI is key to democratizing analytics to broaden the sphere of users to include everyone, from data scientists to non-technical users. Stephanie says, “Cognos is such an accessible way of generating insights quickly from data and providing clients with amazing visualizations, and its AI features are an easy way to introduce clients to its full capabilities. The Explore function helps them generate insights that they would probably not have detected otherwise. It’s like having a great assistant that helps you to consider all the trends in your data.”
Stephanie’s clients also enjoy the driver analysis and predictive analytics capabilities, “once they’ve tasted the AI features in Cognos, they often want to take it to the next level, by using Watson Studio or Watson Machine Learning.” And as data volumes continue to grow, it’s becoming more accepted that the best way to manage and interpret data with accuracy is with AI functionality.
Helping a wholesaler maximize margin
Stephanie’s team recently helped a Dutch wholesaler better understand its revenue from 30,000 SKUs over six distribution levels and three cluster levels. They had been relying on traditional financial management information, which wasn’t timely and lacked margin-and-stock analysis. “The essential question of where they made their money was largely unanswered,” says Stephanie.
Stephanie helped define the scope of the challenge — to provide C-level and level two management with better financial and operational insights, drawing upon multiple databases for ERP and stock information.
By using a secure integrated gateway for Cognos Analytics, Stephanie was able to deliver in nearly real-time dashboards with actionable insights and easy-to-read visualizations. Stephanie says, “We opened up countless on-the-spot deep-dive possibilities, which are now facilitating much more agile board meetings. Most importantly, with the incorporation of the AI and predictive analytics possibilities in Cognos, we could help them answer not only what was happening, but why it was happening.”
For other clients, Stephanie uses Cognos to create dashboards around turnover and gross profit, solve data quality issues (such as a duplication) and combine internal and external sales and market data.
Analyzing more than numbers
With a degree in linguistics, and experience working with unstructured data for Google and Bing, Stephanie understands that numbers only tell part of a company’s story. “Companies analyze their financial data to understand more about the behavior of their customers. But they often don’t analyze unstructured or linguistic data, which Gartner estimates to be 80% of all company data,” says Stephanie.
For a client doing data migration to SAP S/4 HANA, Stephanie is using Watson for machine learning and classification, and Watson Knowledge Catalog for data cleaning and building a business glossary. Stephanie says, “Since we are dealing with multilingual databases, we’ve also used the Watson Language Translator API to translate quickly from the different languages, such as Hungarian or Chinese. We were all amazed how quickly Watson provided high-quality translations on large datasets in such a short amount of time.”
Being an Analytics Hero
To Stephanie, the true measure of success is making clients feel like she’s committed to their goals — that she’s a trusted member of their team and is helping create real change. Stephanie says, “I think my biggest compliment was when I was supporting a team with data analysis. After the team lead presented our plan to management, the CFO told me he saw a real change in behavior from the team lead; that he felt empowered and took more ownership of the project. I felt proud to be part of their organization’s transformation to being truly data-driven.”
“I’m honored to be named an Analytics Hero; it feels like an acknowledgment that we’re on the right track at BOLD. Coming up with great plans isn’t the hard part; executing them is. If you can help a client do both, they will see you as a hero.” Stephanie thinks that success in her work from a data perspective is coming up with solutions to complex problems, such as data quality or data architecture. She describes from a personal perspective, “it’s more about enabling the teams or departments to generate their insights and giving them the tools to excel in their jobs. Data analytics is not just about analysis; it’s also about a new approach to problems.” Stephanie believes that this way of thinking will prepare her users for a future in which these skills will be more necessary, and she’s grateful to be part of their journey.