"Det er vanskelig å komme seg ut av det jeg kaller: et excel-helvete. / It is hard to escape, what I call: Excel-hell."

Are you wondering how medium-sized companies can handle data strategy and data governance effectively? Join us as we talk to May Lisbeth Øversveen, who has over 23 years of experience in the industry, and shares her expertise from Eidsiva Bredbånd. She provides us with insight into how to work with data maturity and the implementation of data strategy.

How can mid-sized companies balance resources and create effective data governance strategies? May Lisbeth and I explore this topic in depth. We talk about the importance of involving the business units early in the process in order to create ownership and commitment around the improvement measures.

Here are my key takeaways:

• The way we talk about data as a profession has changed, the lingo has changed and we adopt to trends.
• To display and evaluate data from different sources that are not connected, excel becomes the tool of choice.
• There is a very calculated amount of resources, that limit your ability to set up substantial teams to work exclusively on eg. Data Governance.
• Data Governance in SME (Small Medium sized enterprises) can be modeled as a repeatable process that incrementally enhances your data governance maturity.
• Identify sizable initiatives, ensure that they can be handled with a set amount of resources, and create metrics that enable you to track your progress.
• You need to find ways to ensure observability and monitoring over time.
• Don’t create something that you have no resources to maintain and improve going forward.
• To identify the right initiatives at the right time, you need to ensure a close collaborating with your business users.
• Ensure transparent and traceable ownership of the initiatives from the business side.
• To create a movement and engagement in data requires continuous and structured communication.

Data Maturity Assessment

• There is a need for speed and agility in SME, to ensure compatibility.
• Data Maturity Assessments are a welcome introduction to ensure that you create a baseline when working with data.
• There are advantages to both an internal view and to get some external perspective on your data maturity.
• Results from a maturity assessment can be a reality check that is not always easy to convey, yet you need to be realistic.
• Maturity assessments should ideally be both
   
  • Modeled/tailored to the needs of the organizations in question.
  • Repeatable and comparable over time and across organizations.
  • Good assessments cover both.
• To initially increase your maturity you can pick different tasks:
  • Low hanging fruits
  • «Duct-taped» operations that you can finally rectify
  • Find known problems that are visible
  • Find pinpoints for your business users
• It is good to start with cases that are understandable for business users, create interest, and can easy show value to leadership - this is what creates buy-in.
• You need to ensure that you keep a clear communication towards bigger, more substantial tasks, so your resources are not limited to quick win actions.

Data Strategy

• Data Strategy needs to be closely aligned with business strategy.
• Have a clear vision of where you want to go.
• To have a structure approach run our data strategy on how to handle both people, process, and technology is important for any work with data.
• Technology is not the staring point, but rather a consequence of your strategic choices, your organizational setup and your available resources.
• You need to include well-defined metrics to track progress.
• Find metrics that are closely connected to business outcome and value creation.