skip to main content

Context

On the interfaces inside and outside the organization within wich digital analytics operates.

You’re not alone
81: Contracts
82: Documentation of work with entity XYZ (agency, team)
83: Globals - Legislation, Ethics
GDPR, Facebook connect
84: Company Culture
Where do Shared Vision, mission and targets end?
Parent company? Office HQ?
83: Communication
Riemann-Thomann-Model, Change Management, …

Externe Schnittstellen 🌐 Digitalisierung & New Work 🗳 Data Democratization 📍 Point of truth 📖 Data Literacy (Alphabetisierung)

Wen verstehen wir als “Wir”? - was ist der context? Das analytics team? Das Product Analytics Team? DIe Online Marketing Abteilung? Das Unternehmen? Unternehmen und Kunden?

How do others interact with different actions?
Democratize Testing?
Data Silos?
Shared Vision, mission and targets? (where does it end? - Parent company? Office HQ?)

Scale of influence:
Data- Aware, informed, driven
See also: https://towardsdatascience.com/data-science-in-the-design-process-754954c996de

Due to the increased amount of readily available data, organisations have come under pressure to utilise their data sets. This pressure is fed down to the agencies that are hired by organisations and designers are expected to support the qualitative insights they collect with a quantified analysis of the client’s data. Hertto (quoted in Likkanen, 2017), a quantitative research specialist, criticises the fact that too many projects are under pressure to gather quantitative data without purpose and end up with “data that is non-actionable from a design point of view”. This is supported by an argument by Esslinger (2017), who criticises that data cannot easily support every design decision. He effectively argues that using data based on past behaviour to shape future product development is a pitfall for many. The example he uses is the case of Motorola, when the company rejected a proposal for a touchscreen smartphone, because market data concluded that consumers wanted to buy phones that were similar to Nokia at the time. Evidently, the designer’s insight was superior to the data-based insight on what should be created (Likkanen, 2017).

Team: https://twitter.com/drsimonj/status/1131567970080178177?s=21