What are the most important factors for sci-tech R&D organizations to consider when implementing a digital transformation? Building a robust dataset? Establishing effective digital infrastructure? Sure, these are essential components—but there may be one you've overlooked. People.
Digitalization offers a wealth of benefits for organizations, including smarter innovation, greater productivity and faster decision making—but these are only possible if the entire workforce embraces the digital mindset. In fact, this is so important, a recent survey from McKinsey highlighted that cultural and behavioral challenges are the most significant obstacles to overcome in the digital age.
So, how can you avoid these cultural pitfalls? We've identified three of the most common behavioral roadblocks that stand in the way of digitalization programs, and we'll show you how to defeat them.
1. Set realistic expectations
Before you develop any kind of transformative digital strategy, you've got to have a realistic vision of what you're hoping to achieve. Too often, technologies like AI, machine learning and digital analytics are thought of as magic wands that can be waved to fix any business challenge. While digital technologies can certainly promote efficiency and accelerate innovation, they only do this when applied in a targeted way.
Digitalization is most effective when it's used to improve workflow efficiencies for well-defined processes. As such, it can be worthwhile to start by implementing digitalization in key areas, such as the core competency of your business. By capitalizing on what differentiates your business from others, you can extend your advantage in that area.
Moreover, there should be a company-wide mindset around digitalization projects. Make sure to gain alignment and set clear and measurable goals. Also, beware of over-hyping the potential outcomes and benefits when justifying your budget allocation. Though this may help make your case for funding these projects stronger at the time, if that vision cannot be realized it will come back to bite you later.
2. Don't put excessive trust in the data
AI is brilliant at analyzing data and spotting patterns far more quickly than humans, but don't expect to see it making business decisions or designing your next R&D innovation. AI excels at performing routine and well-defined tasks that don't require higher levels of intelligence, but it lacks the broader insight required to make complex judgments a human might consider straightforward.
So, when faced with data that's erroneous or unusual, AI won't necessarily have the cognitive reasoning capabilities to know when things aren't quite right. While human analysts might recognize when additional factors are at play, algorithms could continue to process data in the same way, generating meaningless or even misleading outcomes. Blindly following AI-derived conclusions can be risky, and it's therefore important to take reasonable steps to ensure that the fidelity of pipeline data is regularly monitored by human eyes.
With this in mind, it's essential that all members of an organization undergoing a digital transformation understand these limitations. Not only will this instill the confidence to question the validity of conclusions in those acting on AI-generated results, it's also critical in busting a dangerous myth that digital transformation projects are here to replace humans with smart machines. This misconception is harmful for workforce moral and can even prevent organizations from realizing the full potential of their digital investments. After all, colleagues who believe greater digitalization will make their job less valuable may do whatever they can to oppose it. In contrast, those who understand how it will make their own role more interesting and their organization more successful, are far more likely to support this change.
3. Communicate organizational change well
Reaping the rewards that come with embracing next-generation digital technologies is easy—getting there, however, can be tougher. Implementing smart systems and workflows may require departments to adopt new ways of thinking or change long-standing practices. Some teams may be reluctant to share their existing data more broadly due to fears of disruption or data contamination. Others may be unwilling to compromise on proposed solutions because they simply don't understand the benefits. Whatever the cause, for some companies, digitalization projects have the potential to generate a seemingly endless supply of friction.
Ask any executive who's successfully steered their organization through a period of change how best to bring people on board, and they'll tell you: it's good communication. This is true for any business undergoing a major transition, however, it's particularly important for those embarking on digitalization projects because of the many different stakeholders involved in delivering the return on these investments.
Communication is essential in minimizing resistance and maximizing buy-in, and to do this effectively, it's first necessary to explain the “Why?” of the project. What needs are driving the project? How will the organization benefit? And most importantly, ensure you answer the question that's top of everyone's minds: "What's in it for me?"
Once every individual understands this vision, it's time to communicate how you'll get there. In other words, what will change, and what will stay the same? In doing this, it's important that your digitalization strategy is not only well understood but will be universally adopted. This can be achieved by establishing clear specifications and timelines to ensure everybody's on the same page. Even simple measures such as designating a data steward to act as a translator to help departments map their content and processes to new models can be a very effective solution.
Embracing digitalization: Recognizing the possibilities, avoiding the pitfalls
Effectively delivering digitalization programs relies on every individual to play their part, and it's your organization's strategy and culture that will help you achieve this. Ensuring clear understanding of the realistic benefits and opportunities digitalization presents—as well as the limitations of such projects—is critical to achieving a successful transformation.
Download our whitepaper to learn more about the opportunities of digitalization for sci-tech R&D organizations.