Does hybrid working represent a new paradigm for research and development in pharma?

Advanced Workplace Associates founder Andrew Mawson and Chris Hood, director of Consulting, EMEA examine how pharmaceutical leaders can maximise the performance of any virtual or hybrid teams. 

The onset of the current pandemic has caused businesses to change the way they work. For many, the directive to work from home necessitated both a new mental model of going to work and some challenges with getting work done. With the aid of today’s contemporary technology platforms and more attention being paid to people management, many of these challenges have not only been met, but revealed pockets of opportunity and progress which should not be lost when the pandemic finally recedes. We broadly agree that there are some elements of work that have actually seen an improvement during lockdown:

• The ability to concentrate and focus (at home).
• Our networks have widened:  anyone, anywhere in the world is now equally reachable through our virtual communication channels. This was also true prior to the pandemic but it seems that individuals have adjusted their thinking to see access in a more democratic way free from the constraints of physical proximity.
• For many the capacity to address work/life balance seems to be enhanced.
• The reduction of commuting time and the wear and tear of commuting is seen as a good thing, notwithstanding the comments made by some that commuting represents thinking time and a much-needed transition between work and home life.

In parallel, the pharma industry itself has not only been presented with many of these same challenges, but the world has applied pressure on scientists to produce life-saving vaccines. In the same way that business and people have reacted and responded to a life changing disruption, so has pharma been quick to react to the discovery, production, and distribution of bringing new vaccines to the market in record time.

In many industries, the greatest brains are aggregated in expensive, well-equipped buildings where they execute traditional methodologies to invent our future. As much as we support collaborative working, there are examples where an individual’s mindset has been able to flourish alone.

David Patterson, the inventor of the RISC chip, was asked to take over the Post grad department of the University of California at Berkeley. He was faced with dwindling enrolment at the school and a very low production rate in papers. He brought all the professors out of their private offices and led them into an open work area where they made themselves available to others during the core hours. In a remarkably short period of time, the school went from being undersubscribed to oversubscribed and the number of high-quality papers written skyrocketed. The impressive outcomes eventually brought the skeptical faculty around, but it was not easy.

There are a couple of key ideas that underpin successful R&D. The first of these is the definition of ‘Innovation’,which is at the core of research and development endeavours. Innovation is the sum of ‘ideas’ generated by creative or divergent thinking. To be innovative, you need both, and the more ideas generated the better. The teams made up of a variety of skill sets, knowledge and views will be more successful than teams that don’t. The extent of this frequency and diversity of communication is easy to measure using social networking analysis. SNA methodology and software allows us to benchmark organisations with three simple KPI’s but also to graphically show the extent to which a group may be silo’d. An example of the ‘anonymised’ output is shown below.

R&D organisations have implemented various laboratory and office workplace measures to respond to the safety concerns associated with this deadly pandemic to increase the universal measures of ‘social distancing’, hand sanitisation, face masks etc.

Some of these include; only allowing ‘essential’ staff back to their workplace, dividing the workforce into two or three shifts, pairing scientists together with one doing the experiment in the laboratory, and the other doing the data analysis from home. Despite the procurement difficulties to the supply chain caused by Covid (and Brexit), organisations are becoming increasingly concerned with the lack of spontaneous collaboration or tacit knowledge exchange. Resulting in a serious impact to their product pipeline three-five years from now.

Measures that help to mitigate against the above include;

• Buddying up staff with a weekly direct chat with others in their organisation (or an individual in an external partner university/company) and setting up internal teaming to mentor individuals to force safe diverse communication.
• Using start-up incubators and graduate companies teamed with the local ecosystem to energise the existing teams.
• Using an effective resource management system combined with real-time occupancy and equipment utilisation monitoring to optimise the workload execution.
• Implementing effective equipment maintenance programs and supply chain management to increase the resilience of the operation. This includes the use of VR to minimise the number of people required on site.
• The use of logistics automation to increase ‘walk-away time’ from experiments to safely extend the working day.
• The upgrading of R&D workplaces to provide more future adaptability attracts key local talent to a vibrant community and adds to the asset value of the infrastructure.

With some organisations seeing only a 10% return of workforce into office space and less than 60% returning to the laboratories, it's clear that decisive steps need to be taken.

R&D companies are all on a similar journey in their aim to create an integrated, data driven lab of the future, and putting scientists at the centre of this vision is key. For some, the focus is ensuring data is accessible to anyone, everywhere. For others it's about creating an environment where people want to work because it's different from other pharma companies. 

The biggest challenge is achieving instrument integration to process data and changing the culture of a company. Some companies have managed to overcome this by restructuring teams or embedding new functions. For all companies it seems that they recognise the difficulty in getting talent with the right set of skills, highlighting the need to bring academia on board and create a culture where business needs can be met. Creating an environment which puts scientists' needs first, enables data generation to be accessible, retrievable, and findable.