MetaDAMA - Data Management in the Nordics
This is DAMA Norway's podcast to create an arena for sharing experiences within Data Management, showcase competence and level of knowledge in this field in the Nordics, get in touch with professionals, spread the word about Data Management and not least promote the profession Data Management.
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Dette er DAMA Norge sin podcast for å skape en arena for deling av erfaringer med Data Management, vise frem kompetanse og kunnskapsnivå innen fagfeltet i Norden, komme i kontakt med fagpersoner, spre ordet om Data Management og ikke minst fremme profesjonen Data Management.
MetaDAMA - Data Management in the Nordics
2#15 - Steen Rasmussen - The Business Impact of Data Ethics (Eng)
«Infants with guns!»
Are we mature enough to track, collect and handle data responsibly, according to ethical standards? I talked with Director of Data Innovation at IIH Nordic Steen Rasmussen about the Business impact of Data Ethics.
Here are my key take aways:
- If were track, collect, and keep all data for any random opportunistic purpose, we put your companies at risk.
- This includes a «commercial curse» of budget-heavy tracking and budget-light management and business value creation through data.
- ROT, Norwegian for clutter, is an acronym for Redundant, Obsolete, Trivial - the dat that clutters your way to find valuable data.
- Collection and tracking of data is still too much dependent on people: If there is a change in personal, you get situations where new people «clutter the clutter»
Marketing & Sales
- For many companies it was Marketing & Sales that drove the data-driven agenda.
- The big value of Marketing & Sales is to add the market-dimension to the data.
- You can actually relate your product to the market, ship to where the market is.
- Analyzing market data is «putting a fixed entity on a moving target». The market changes to rapidly to provide good analysis.
- The more you push behavioral forecasting into the future, the bigger your uncertainty.
Business value & Ethics
- Corporate irresponsibility is an issue.
- Sometimes we get involved in a projects for the projects sake.
- Data projects have for a long time been theoretical, so the impact was not visible.
- Chat-GPT is a black box. Should we really give it more firepower, if we don’t know how it works?
- The market determines that there is a business value in being first.
- The speed of innovation doesn’t give time for reactive regulatory bodies to regulate efficiently.
- Companies need data ethical guidelines to say, how they will, shall and can use data.
- Who should define data ethical guidelines in a company? It is still done on a user-level, whilst senior management is looking at market situations and weighting them against ethical guidelines.
- We need regulatory and top-level guidelines that cannot be bent according to market situations.
- «Ideally, but highly unlikely we need a global set of data ethical guidelines.»
- The more trustworthy you are as a company, the more relevant data is shared with you.
- With that trust and data, you can understand the market better than companies that are not trustworthy and basically flying blind.
- Personal Data Literacy is important, and we need basic digital skills in our society.
- There is also a lack of understanding, when it comes to measures set in place for peoples benefit, eg. Cookie-banners.
- We are still lacking good privacy approved alternatives to the tools we are using on an everyday basis.
- Everyone has to follow ethical guidelines. We cannot have a DarkOps department in our company.
- Data Ethics guidelines should be something everyone can refer to.
- Ask yourself: What is the minimum of data we require to collect? Anything else should become an ethical question.
Data Protection Laws:
- There is a difference between the interpretation of regulations in the EU.
- Nordic countries interpret law relatively, is this just, fair, reasonable?
- Southern European countries use a more napoleonic or dogmatic approach, where «the law is the law, and the law must be obeyed.»
- Both Chat-GPT and Google Analytics have been handled differently by data protection authorities.
- Data Protection Authorities generalize to much, and don’t look at differences in technology.
- Is a strict, generalized interpretation creating panic, for users of eg. Google Analytics?