Data and Analytics Lead, Finnair
Minna Karha is a passionate data culture coach with more than 15 years’ experience of leading data and analytics teams and developments in the media and aviation sectors. She recently discovered a passion for using design thinking with facilitation tools to support dialogue between business, technology and data professionals.
In her current role, Karha leads Finnair’s company-wide data and analytics strategy. She’s tasked with enhancing the efficiency of business processes with information-driven decision-making and improve customer experiences via personalization.
She is focused on facilitating and orchestrating a data literacy culture across the organization, to strengthen staff data skills and create a culture where everyone has easy access to relevant information and knows what it means for their work.
Karha’s skills include promoting fact-based decision-making, data-driven process optimization, making data and analytics understandable to business professionals through working as a ‘data translator’ and highlighting the importance of ethics-by-design in data solutions development.
Getting to know...
Minna, how are you working to demystifying data for your wider-organisation?
For this year the goal is to bring awareness and build responsibility towards managing data and utilizing it for business value with the right focus. In practice this means we are now:
First: including data to be identified (using conceptual data entities) and documented along with our business processes (data created and data needed in the process). We are currently working on developing practical methods with our strategy team. This will help us to see better how data clues the business processes together and also can be used as a tool to find the right places to improve the utilization data & analytics to help business decisions and efficiency.
And second: utilizing design thinking to identify the right problem to be solved – and the right solution to solve it. This helps us to ensure the actual development efforts for analysis and models are focusing on building correct solution to match the actual business problem and the business teams to see what kind of problems analytics and data science can solve, besides delivering reports and KPI dashboards. This also motivates the data & analytics teams as they will collaborate closely with business colleagues and be able to bring their knowledge on the opportunities of utilizing modern tools to the planning table.
And third: Implementing DataOps and ModelOps to our practices to secure business continuity, reliability and time-to-market. As data is generated everywhere in the organization, in all processes and advanced analytics needs to be also utilized in various processes, we need to secure the way of working allows us to re-use, scale and adopt new capabilities fast. The analytics services and products need to form a consistent entity where recommendations and KPIs are complementing each other, fueling the business in an optimal way. DataOps and ModelOps enables us to deliver faster and manage the lifecycles so that we can focus on building and maintaining only the value-adding analytical products, the ones that are actually used and solving the problem they are meant to solve.
Minna, you’re passionate about encouraging people from all backgrounds to get involved in data and analytics, what sparked this passion for you?
We are all citizens in a digital world – which is fueled by data. Data can do lot of good for us as individual consumers, as businesses and as citizens. This also sets responsibilities to us: we need to understand how data is created, what is our role in it and understand how it can- and should be used in different situations. Being data literate means one understand what data is used when we use data empowered services, at work or as citizens, how it was created and how it is processed to fuel the service. If we do not know this, it can become intimidating and have a negative impact instead of serving the purpose.
At work I have also seen that it is not yet fully understood that providing well-managed data, and knowing exactly how those recommendations and proposals are created, is everyone’s responsibility in their own role. For the future, this needs to be changed. No-one acting in a business process can outsource the data quality to someone else, nor can anyone using an analysis outsource the knowledge about what influences the outcomes.
This is a culture change that is very much needed, requiring the same kind of skills as being able to read, this is why I especially like the terminology “data literate”.