Why the resilience of your research matters more than ever

The biopharma industry continues to endure some of the most turbulent and difficult market conditions in a decade. Within this environment, staff turnover has become an essential conversation.

‍Beyond recruitment budgets: the hidden costs of staff turnover

Staff turnover, when voluntary, is not inherently bad. On an individual level,this can indicate career development and new opportunities for growth. For the organisation, it can be an opportunity to address missing skillsets or introduce new ideas into the business. And at a community  level, the frequent movement of skilled staff between companies can accelerate innovation within a collective ecosystem.¹ 

But there is always a cost to change, and the loss of institutional knowledge is perhaps the best example of this. Within any company, there’s a wealth of tacit knowledge that’s rarely written down. In a biotech company, this might include the original reference for a DNA sequence that’s been used in a particular plasmid design for years, “the knack” of getting a complicated machine to behave properly, or the reason why a protocol is always run one way and not another. 

Individually, perhaps these examples are no big deal. But collectively, they pose a significant operational risk that compounds with scale, and translates to lost time and duplicated effort. The International Data Corporation has quantified the financial impact of this, estimating that a company of 1,000 knowledge workers loses up to $2.5 million per year to time spent searching for information that is not centrally stored, and a further $5 million per year duplicating work that already exists somewhere in the organisation.² In a biotech, that means duplicating failed experiments, absorbing reagent costs twice, and spending months of research time on questions that have already been answered (in the negative). This contributes to a pattern of avoidable waste that can consume up to a staggering 85% of biomedical research investment.³

Is digital transformation the solution? Or creating a bigger problem?

Isn’t this the exact problem that digital transformation promised to solve? Well, yes. But in many cases, the “solutions” are in fact causing more problems. Now we’ve got too much data, and too many tools. Is that document on your local drive, on One Drive, or saved as a Google Doc? Did you share it on Slack, on Teams or via email? Is it uploaded to the project management portal or Dropbox? And which version exactly is the latest? 

The reality is that most biopharma companies are dealing concurrently with two separate, but related, problems; both of which become more apparent during times of change. First, how to capture and document knowledge that isn’t usually recorded, to protect the company’s science and collective experience. And secondly, how to store it in such a way that it can be easily found and retrieved. 

‍Effective digitisation requires quality over quantity

A new generation of lab software is designed to weave all the different strands of a typical research project together, rather than adding another technology into the existing stack. This means connecting the in silico design of a construct to the protocol used to make it, the samples produced in the process, and the data generated along the way, thus building a robust scientific record that includes all the experimental context that might otherwise never have been captured. 

So how to decide if such a system is an improvement on existing disconnected tools? A couple of simple tests should provide the answer. 

1. Can a new team member easily find out why the lab uses this vector and not that one? 
2. Can a senior executive see, at a glance, which projects are progressing as planned, and how resources are allocated?
3.  Can a company preparing for regulatory submission quickly demonstrate a complete, unbroken chain of evidence from sequence design, plasmid and cell line to viral vector and associated data? 

In a well-implemented system, the answer to all three should be yes.

Staffing changes create specific compliance vulnerabilities in some biopharma environments. For example, ensuring that records stay contemporaneous with physical operations, even when headcount is low; making sure that training records don’t fall out of alignment with electronic signature authorisation, and maintaining adherence to SOPs even when the original author has moved on. A connected digital record helps mitigate these risks by making audit-ready documentation a byproduct of the lab’s day to day operations.

The bigger test of a new digital solution is always whether scientists actually use it. If software is difficult to navigate, clunky to operate, or slows people down, it won’t deliver on its promised solution. The real advance in second generation software is usability; that is, becoming a technology that makes scientists’ lives easier by adding value to their work and freeing up their time, because no matter how good the software is, it’s the people in the team who will both deliver and derive the value from it.

When this sort of resilience is baked into the scientific workflow, change becomes easier to manage. Team members moving on to new opportunities don’t take years of unwritten knowledge with them, or spend their last days in the lab frantically scribbling down handover notes that leave glaring omissions. New team members inherit a full scientific history, and a clear understanding of the direction of travel, rather than a folder of disconnected documents and a freezer drawer full of chaos. Their learning curve becomes shallower, and the time it takes to get up to speed shortens. 

‍Strategies shift and markets evolve. Science must stay resilient.

These are difficult times for the biopharma workforce. For those scientists navigating a job market that has rarely been harder, the professional and personal cost has been significant. But these are exactly the moments when small cracks in the scientific record can start to widen. Those scientists, teams and leaders who now have firsthand experience of what it costs when institutional knowledge walks out the door, are precisely the people best placed to build a more resilient future. 

Markets evolve and funding cycles turn, but good science holds firm. A robust digital infrastructure should be considered an essential element of a company’s scientific foundations to make sure this holds true.

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Read the full article in Innovations in Pharmaceutical Technology

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References

1. Saxenian, A. (1994). Regional Advantage: Culture and Competition in Silicon Valley and Route 128. Harvard University Press.
2. Susan Feldman and Chris Sherman. The high cost of not finding information. An IDC White Paper.
3. Chalmers, I. and Glasziou, P. (2009). 'Avoidable waste in the production and reporting of research evidence.' The Lancet, 374(9683): 86–89. DOI: 10.1016/S0140-6736(09)60329-9.