I love data. Facebook, LinkedIn, digital photo libraries on iCloud, cloud for my music, Evernote, Dropbox and OneNote, not to mention my email archives, document archives and other files. They all have different purposes, however, all of this data is really important to me personally or professionally and if I lost some of it, could not read it or access it, it would cause me almost physical pain. Having been involved in the legal discovery process, I also understand the value of being able to easily search this data. Much of this data increases in value for me over time.
The thing is that I really care about my data and partly that is because my professional life has always been heavily focused on data and its value as a scientist and a business person. I now work for a company that really cares about long term data management and integrity so it’s not surprising I think about it, a lot.
Strategic buy-in to make cultural changes is not so simple
However, trying to explain the importance to your organisation and getting strategic buy-in to make cultural changes is not so simple. Data breaches, data loss, cyber-attacks and so on all create compelling events, but often solutions paper over long term sustainable approaches, especially as there are costs involved and it’s not typically seen as a core part of your business.
Over this series of blogs, I will discuss the four big economic drivers and the associate fallacies that can be de-bunked which could help you, or your organisation rethink an approach to data for long term data preservation and integrity.
This series will discuss these economic factors and the challenges in context to an executive level in a company for the pharmaceutical industry and associated services and biotech companies that work and operate in this industry. However, it is actually applicable to all of us and our businesses wherever we work.
The four economic factors are:
- The demand for long term digital and data life cycle management is a derived demand.
- Digital materials are perceived to be depreciable durable assets.
- Digital assets are often non-derived in consumption and create a free-rider potential.
- Long term data management is temporarily dynamic and path dependent.
These are classic economic principles and each of these is the standard position with regards to data, I argue that all of them are wrong for a number of different reasons. These reasons relate from the beginning of discovery R&D all the way through to end of life of data for both regulatory, legal or IP purposes.
The next article will explore the first economic factor in detail and in context to the pharmaceutical and life sciences industry.
