To achieve digital transformation success, quality control (QC) labs first need to prioritize cultural transformation. A lab’s culture can often be decades-old, but it requires a transformation that mirrors the technological advancements taking place around it.

This agile shift in culture, moving away from the standard waterfall methodology, can start with an individual department or a team on a trial basis and gradually spread to the entire organization.

More than the change in skills in the workforce, what becomes important is whether the decision-makers believe in and can drive the necessary change, or whether they want to stick to traditional ways of executing organizational work.

Once a cultural path forward is established, an organization needs to focus on achieving certain goals. These goals include developing new workforce skills, engaging employees, delivering excellent customer service, improving safety and fostering leadership excellence that can be used as touchstones throughout the process.

A successful cultural transformation requires full engagement from all levels of leadership, which plays a vital role in sustainable modelling and coaching the desired behavior that will permeate through the organization. This requires creating a roadmap that addresses questions like where the organization is right now, where it wants to be, why it wants to change and what is in its line of sight.

To determine how the organization perceives the company culture, surveys, focus groups, interviews with high-potential employees, one-on-one interviews with executives and digital voting platforms are areas that can help gather successful information from across the organization. Before moving onto the next step in this journey, accuracy in data and inputs becomes an important factor in decision-making.

Based on the data and inputs gathered, organizational goals and objectives can be aligned with the introduction of new-age technologies, such as artificial intelligence (AI), machine learning (ML), digital twins and data and analytics (D&A), among others.

How technologies are transforming organizational culture

In Deloitte’s State of AI in the Enterprise research, it stated that organizations that invest in change management are 1.6 times as likely to report that AI initiatives exceed expectations and more than 1.5 times as likely to achieve outcomes than those that don’t.

AI-fueled organizations leverage data as an asset and aim to scale human-centered AI across all core business processes. They use rapid, data-driven decision-making to enhance both the workforce and customers experiences. These organizations typically do more than trust data; they demonstrate a willingness to quickly turn insights into action with rapid experimentation, which is crucial in a QC environment.

“AI and ML will play a big role in improving the digital and cultural transformation in the laboratory, especially by improving a lot of business cases. After connecting the devices, what becomes most important is the smooth availability of data in real time and the ability to analyze the common mistakes and failures that can be predicted before even starting the DSA [digital subtraction angiography]. The only possibility is by using AI and ML,” says Joseph Laraichi, Director and EU Lead for Life Sciences and Healthcare IoT at HCLTech.

An MIT SMR-BCG report mentioned that the AI benefits go well beyond improved efficiency and decision-making, enabling organizational effectiveness, strengthening teams and enterprise cultures, generating cultural as well as financial benefits. These cultural benefits can penetrate the foundation of business operations, improving assumptions that drive organizational behaviors and ensuring the pursuit of smarter goals. Executives familiar with AI implementations in their organizations presented a clear message that business culture affects AI deployments and vice versa.

The report highlighted that more than 75% of survey respondents saw improvements in team morale, clarity of roles, collaboration and collective learning. Some respondents who saw significant financial benefits from their AI initiatives were 10 times more likely to change how they measure success than those who saw no such benefits.

Besides realigning behaviors and improvement in competitiveness among employees, in some cases, AI helped leaders identify new performance drivers, which led to new assumptions, objectives, measures and patterns of behavior, along with new areas of accountability.

Driving cultural transformation in a quality control lab

During a digital transformation, the question that often arises is how organizations can instill a common cultural transformation and ensure everyone is brought on the digital journey.

According to Laraichi, one of the biggest challenges today in the pharma or MedTech sectors’ digital journey and in the laboratory specifically, is that the lab engineers are overloaded. They are aware that a lot of tasks can be improved and automated within the protocol process, but they lack the time to engage with it.

“QC labs should focus on ‘how we instill digital transformation through culture and create the right environment for the scientists to dedicate time and resources’, because often many lab engineers complain they have very busy days and don’t have time for out-of-the-box thoughts or how to improve what they have already been doing,” says Laraichi.

He adds: “Prioritization is one of the key factors to consider. For example, data wrangling is the heaviest task in the labs that leads to data errors. Usually, we start by talking about this use case, while using risk management tools to evaluate the risks associated with this change and support the decision-making.

“So, to instill a cultural transformation and onboard people on the ground to adopt the mindset of digital journey, we listen to every lab employee to gather their feedback on how the specific process can be improved to maximize the value of change.”

In addition, developing, upskilling and reskilling employees in data-literacy skills as part of the culture builds confidence and a deeper trust in new technologies and models.

Defining success

The definition of success in a digital and cultural transformation journey doesn’t have a destination. It’s a continuous journey that revolves around an enterprise’s practices—not just “doing digital” but “be in digital”.

“HCLTech is the right partner with both expertise in scientific labs and as a technology integrator to support the digital journey of Life Science labs,” says Laraichi.  

The role of HCLTech is simple: Help its pharma and MedTech customers to evaluate the priority use case with the highest ROI and accompany its smooth integration while improving the quality and patient safety and reducing the business risks.