22 May Thoughts after DAM New York 2019
DAM New York 2019 is now in our rear view mirror and it’s taken some time to fully process the experience. Attending as a sponsor requires a lot of preparation. It’s as if you’re throwing a party, cooking dinner, singing and greeting guests all at the same time. Still, we were excited to learn and collaborate with other DAM enthusiasts. Librarians, archivists, designers and more- we had a great time, met interesting people, learned lots and were absolutely ready to hit the ground running (after a weekend to rest). There’s a lot to unpack but here are a few observations after this event.
Useful AI in DAM is right around the corner
Artificial Intelligence is at the forefront of just about every technology gathering today. Gatherings such as the Henry Stewart DAM event are integral for the development of this cutting edge capability. We heard ups and downs of allowing AI to identify objects and tag content. In my experience, the most successful application is with a touch of machine learning (ML) and a hint of human intervention. The balance between AI/ML and human intervention is going to be a delicate one. A slight error can take the AI into a tailspin of poorly tagged content. Too much human intervention becomes counterproductive. We’re seeing machine learning take large strides to close the gap between what has to be trained and what’s ready ‘out of the box’. I’m excited to see how this technology develops. For now, I see digital workers playing a big role in augmenting the ‘human’ intervention as this application of AI is fine-tuned.
It’s not about the feature, it’s about the result
Yes, I realize my last observation was about a technology feature. At the end of the day, the technology we use is a tool to enable results. It’s a tough idea to completely embrace. Most people who attend a conference on Digital Asset Management are genuinely excited about where the industry is going. We get fixated on every new feature and all of the shiny new objects. This is the kind of passion that makes these events so much fun to attend. It can also be a barrier to adoption. Our users haven’t spent their professional lives understanding the impact of governance on scaling across the enterprise or why metadata matters in your archiving strategy and measuring campaign performance. Instead, our users have their own work to do and their own goals to accomplish. Unless we can show how it impacts the results, each feature is just a button that may end up skipped or worked around.
Governance without adoption is just a bunch of rules
During a panel session, someone asked me about how to actually get your users to buy into your governance model. In fact, this question was asked many different ways throughout the conference. The usual formula for implementing DAM is Scale = Structure + Governance. You figure out how it works on one team, document it and use those steps to bring on the next team. Rinse and repeat until you’ve taken reached every team and it’s instant scale, right? Well, that’s how governance grows. That’s how you grow the rule book. We need people to use the DAM to say we’ve really achieved scale. My response to gaining buy-in was simple: try to avoid saying “you have to”. To some extent, it’s really that simple. In practice, however, it’s much easier said than done. The reasons we face resistance vary greatly between groups and individuals. Sometimes it’s about understanding the bigger picture, other times it’s about enablement or awareness. There’s no hard and fast rule for making sure adoption happen smoothly. It’s a matter of understanding people and managing change. We’ll be exploring this topic in greater depth during a roundtable discussion at DAM Europe next month. I encourage you to stop by and listen to others’ experiences with this very topic.
If you won’t be in London or have comments/questions, reach out via LinkedIn or email me at firstname.lastname@example.org