Dna fingerprinting

The majority of life sciences organisations in Europe experience problems when considering how to improve data quality, according to a new survey. 

“Data quality” refers to such things as the accuracy and precision of information, and it is considered to be of a low standard when the data is – for example – inconsistent, incomplete, or missing.

There are a variety of ways in which the quality of data is measured. Here is an example methodology, produced by Dama, which lists the following criteria:

  1. Completeness
  2. Uniqueness
  3. Timeliness
  4. Validity
  5. Accuracy
  6. Consistency

Bad information, or low data quality, can lead to bad decisions, and can, over time, negatively affect enterprise management.

Moreover, because life sciences is the study of living organisms and related material and has applications in healthcare and security services, data quality in this essentially scientific endeavour is arguably much more critical to this sector than others.

The Veeva 2016 European Customer Data Survey (infographic pictured below) questioned more than 80 life sciences companies across Europe, and found that more than four out of five respondents – approximately 87 per cent – face challenges in how to improve data quality.

The reasons for the data quality being low, says Veeva, is mostly due to limitations of their data vendors – which 41 per cent gave as their problem – and siloed data across multiple systems – 38 per cent.

Respondents also cited outdated stewardship and approaches to technology as difficulties, including data steward services that are inefficient or non-existent – 36 per cent and outdated or incrementally developed data management technology – 30 per cent.

Veeva says these challenges exist despite the industry’s recognition that quality data is key to effective commercial execution. Respondents cited increased sales and marketing efficiency – 77 per cent – and improved analysis and decision-making – 76 per cent – as their top needs of customer data.

Yet only half of those surveyed are currently satisfied with the quality of their data. As a result, three-quarters – 78 per cent – of respondents report they now have customer data quality initiatives in place or will within two years, as their organizations try to close the gap between what is needed to operate effectively in a multichannel commercial environment and the current quality of their customer data.

Guillaume Roussel, director of strategy, Veeva OpenData, Europe, says: “A major shift is underway as European life sciences companies focus on improving data quality and timeliness as a way to increase commercial effectiveness.

“We are seeing an urgency to close the gap between how customer data is currently sourced and managed and the new business imperative for greater speed, productivity, and orchestration of customer experiences, especially across communication channels.”

data quality infographic

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