For the past decade, one mantra echoing through the hallways of corporate headquarters around the world has been the need to be data-driven. The philosophy behind this shift was that if businesses measured more, their strategies would be better informed. The natural end result would be better business decisions and accelerated revenue growth. It’s not a bad story, really. It’s logical and sensible. It seems to pass the “sniff test,” as it were.
There’s just one problem: collecting information and using information are two very different processes. In a world where workers and corporations alike struggle to manage the information they already receive, what good will this do? In an environment where silos, specialists, and consultants have fragmented company expertise, I can’t help but be worried by this modern-day house of cards.
There is no doubt that the more informed a decision is, the greater the likelihood of its accuracy. But one critical piece of information that’s been lost is perspective. No one can see across all the silos and segments – even if you gather armloads of new information, it won’t truly synergize all the pieces of the business. We can see this problem currently, particularly in healthcare.
As more and more information was collected, expertise grew narrower. It became clear that the human brain could maintain only a certain amount of the information thrown its way, so we kept customizing our work to encompass the information we could use. In medical specialties, we went from developing oncologists to breast oncologists to radiation breast oncologists to, most recently, an oncogenic pathway-specific oncologist. This same overspecialization has occurred in the corporate realm as well; the only response to increasing complexity was to narrow expertise to small enough realms that a person could reasonably know “everything.”
Rapid Learning Models Stretch Knowledge Further
Of course, it’s unrealistic to think that anyone could know everything about his job. That implies we live in a static, unchanging world; nothing could be further from the truth. Instead, we should turn to information management. Businesses who utilize rapid learning models thrive in times of information overload because they’re engineered to simplify information and learning. Their more traditional counterparts struggle with change because it stretches the infrastructure they’ve built to closely align with what they currently know. It’s a dangerous way to run a business.
In leading healthcare organizations, such as the National Cancer Institute and the American Society of Clinical Oncology (ASCO), tremendous resources are being committed to these initiatives. They recognize that rapid learning systems are designed to do two things: 1) they bring information together so it’s immediately available to inform future decisions, and 2) they leverage search-based and social technologies so explicit knowledge (objective realities), tacit knowledge (experiential lessons), and context (meaning) are readily available.
In medicine, it’s conservatively estimated that as many as 80% if decisions are made without the support of definitive evidence. This is largely because definitive evidence doesn’t exist. This is a frightening reality that explains why we call it the “practice” of medicine. Few would argue that in business, the number probably skews closer to 90%. Rapid learning systems provide more effective and efficient means of synthesizing the tacit lessons and context so they can be balanced with explicit knowledge in a way that breaks down silos and re-envisions organizations.
Moving Your Company Forward
This is not to say that perfect rapid learning systems already exist. But new ways of data acquisition and management must be explored. It isn’t enough to be content with vast separations of knowledge and understanding across a company. This ensures that people will never make solid, forward-thinking decisions because they will be taking into account only some of the information they need to do their jobs well.
So what can you do now? Keep these four ideas in mind as you make strategic tactical and hiring decisions for your business:
- Stop hiring specialists unless absolutely needed – be aware that the more specialists you empower and the more project consultants you employ, the more you are exacerbating the knowledge silos within your organization.
- Build channels for communication across the organization – the simplest rapid learning model is a social learning model. Give people opportunities to speak and share their expertise, and knowledge won’t be hoarded amongst those who already have it.
- Accept rapid learning as a critical element of your company’s culture – make it a point to emphasize continuous learning and expansive knowledge in your company. If employees know that they’re expected to keep up with their colleagues’ learning, they’ll make it a priority to absorb and question as they work.
- Re-engineer at least one decision-making team per quarter – a rapid learning culture must be established within the business process before it will pay dividends. To do this, incorporate new perspectives and layers of expertise within your decision-making teams. This will prove to everyone – specialist or not – that each role on the team is essential and has something to offer the larger group.
Healthcare may already be moving toward rapid learning business models, but this trend shouldn’t be isolated to doctors. Corporations fulfill equally vital needs, and businesses must treat their objectives and workflows as the collaborative tools they are. A company is only as strong as its narrowest worker. If he learns from his colleagues and teaches them as well, the organization gets stronger. It’s a system that maximizes what you already have at your disposal – and that’s a real return on investment.