Tag: pharma

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10 May, 2019

5 ways to reduce the increasing cost of compliance across your life sciences organization

Sreedhar Tulluri

Compliance is a necessary requirement of doing business within the life sciences industry, and rightly so. However, for life sciences organisations it is costly and complex and…

17 May, 2018

Blog series (part 4): The final economic fallacy of long term data being temporarily dynamic and path dependent

Daniel Hickmore

The final economic fallacy is that long term data management is temporarily dynamic and path dependent. I would argue that data is certainly temporarily dependent, but not path dependent. Data is constantly degrading in every temporal dimension; the past, today and..

15 May, 2018

BioIT World 2018

Greg Macdonald

Don’t miss Arkivum at this year’s BioIT World, taking place in Boston. Come and meet Daniel Hickmore, our VP of Pharma, Life Sciences and Healthcare and Yaron…

09 May, 2018

Blog series (part 3): The economic principle of data creating a free rider potential

Daniel Hickmore

In previous blogs we talked about data appreciating in value over time and that data is not a durable asset but very fragile. Data is not a durable asset like a house, but more like a very fragile oil painting that needs to be very carefully looked after and maintained with lots of…

03 May, 2018

Blog series (part 2): The economic principle of digital data being a depreciable, durable asset

Daniel Hickmore

In my previous post, I outlined the four key classic economic principles and how incorrect assumptions associated with them for long term data management could actually be costing your organisation money. 
The four economic principles we are discussing..

01 May, 2018

Blog series (part 1): The four economic factors that make the “cost of doing nothing” more expensive than “doing something”

Daniel Hickmore

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.