🔍This week we delve into digital forensics and explore how organizations can use challenges they face with data pipelines as opportunities for building collaborations across staff. How does your organization deal with staff departures? Have you ever found yourself wanting to talk to the person who collected a piece of data, or first developed the metric or instrumentation? What could you discover about your organization and team by adopting the mindset of a forensic technician?
🔮Next month we’ll be running an Oblique Thinking Hour (OTH) where we’ll co-create a futures card deck and try to play a round with it all within a 60-min call. Come with ideas about what areas you’d want to build a card deck around, we’ve recently built decks for African Open Science and Aotearoa (New Zealand) Futures. This will be similar to the deck we used in our very first OTH which you can read about here. Details and signup links are at the end of this email.
👀 Something that caught our eye
The process of figuring out what data to collect, how to store it, and what analyses can be conducted can be complicated. Often, these decisions are made by different people at different times in the organization's history, each with their own unique needs and goals. As a result, the resulting data can be disorganized and difficult to make sense of. And when team members who understand the data leave the organization, or the organization's priorities and data practices change, it can make things even more challenging.
This week we’ve been thinking a bit about digital forensics and how we might apply it to help organizations understand and enhance their data-driven practices. We began considering this idea because Dan has recently been working with a trove of operational data from a startup robotics firm for a study of new automation development. Working with this data is difficult (for research purposes, anyway) because the organization continually shifted the types of data they generated as their technology evolved. Complicating matters, the ways in which data collection took place changed over time too, making it challenging to reconcile old data with new data in the process of doing any kind of meaningful analysis. All of these features are more prominent when an organization is developing a new or experimental system, figuring out what data is important to collect, which is not, and which data management practices make the most sense in service of the organization’s goals.
Understanding the changes constitutes a form of digital forensics, a loosely-connected set of techniques for finding, analyzing/interpreting, and organizing evidence from digital devices (most often thought of in the context of criminal investigations). Other applications of the techniques include examining scientific research processes and results and conducting insurance fraud investigations.
We believe the techniques may also be useful for helping to create culture and strategies for a data-driven organization: making use of old data, getting people talking to one another about data, and prompting organizations to be more intentional about their data practices.
Consider this: You have a coworker who has solely managed your team’s data practices for years. The coworker abruptly leaves the organization and is unreachable. Remaining members of the team have all collected, accessed, and used data in different ways depending on which part of the proverbial elephant they touch. How do we take individual understandings and combine them into a shared intelligence to replace the existing coworker and be better data stewards going forward?
As mixed-methods people, we at OrgMycology lean on qualitative interviewing techniques as a first step when we do related types of exploration for research and consulting work. Interviews enable the organization to document what each person knows about the data, where gaps exist, and what might be improved. In Dan’s work with the robotics data, for example, he used interview transcripts from a range of employees to understand why data practices changed and what the impact of those changes were on the organization’s development efforts. The findings from that exercise then informed how he understood and made use of seemingly disjointed, irreconcilable data.
Building on the interview responses, you might then think about facilitated group discussions and digital forensics-inspired activities that get people working with one another and developing strategies for the organization’s data. The exercises you might go through in this process have very positive follow up effects. Beyond getting people to talk to each other and build relationships, everyone involved learns about the expertise of their coworkers. Likewise, they can generate ideas for improving the organization’s data pipeline, develop shared standards for data management, and find creative ways to make use of “outdated,” “stale,” “irrelevant” data that their forebears worked so hard to collect.
Engage with us
May Oblique Thinking Hour May 10th / 11th (depending on timezone)
In this Oblique Thinking Hour we'll co-create a card deck for prompting futures thinking sessions. As a large group we'll pick a theme, brainstorm cards, and break into small groups to write the text for the cards. Then we'll come back together and play a round of futures thinking in breakout groups with the deck we just made 🤯. These cards and this process can be used to build a unique prompting deck for other groups, and can be a great exercise for building futures thinking and group cohesion in many types of organization. You'll come away with strategies for helping your team or organization think about what it wants the future to look like and develop ideas for how to get there.
Two times are available
May 11, 2023 at 8:00 AM in Pacific/Auckland timezone (May 10th, 8pm UTC)
May 11, 2023 at 8:00 PM in Pacific/Auckland timezone (May 11th, 8am UTC)