Reframing the KM discussion
One thing for sure in the current world of uncertainty is that the tech sector is growing fast and set for a new dot-com boom. This means there will be a year, if not several years, of opportunities for innovation in information and knowledge management. As the office’s physical and psychological boundaries broke down through the course of the pandemic, the reality, permanence, and challenges of working at home and in situ have taken hold.
As a result, mobile capture integrated with robotic process automation is already seeing a significant boost of interest. Blockchain has at its core decentralization from a technology perspective and also plays well in this new reality, securing and verifying content wherever it may be. The current tech growth is underpinned by a surge of activity to drive self-service—be that self-service for the customer, the partner, the employee, or suppliers. Yet, without thorough business analysis, insight, proper planning, and a focus on challenging the better-quicker- cheaper approach and replacing it with a beneficial-adaptable-affordable commitment, there is a world of trouble ahead.
We may in fact, end up with a boom that in 5 years’ time leaves us with more complexity and problems to unravel than we have today. It’s a difficult situation; the tech market is booming, but the economy is not. Short-term thinking and quick fixes to today’s problems dominate. Still, a little planning and strategic thinking will go a long way to ensure that today’s quick fixes lay the foundation to, at the very least, remain adaptable to future change, benefit everyone, and stay within budget.
For decades, professionals in the tech sector have talked about service-oriented architectures; the buzzword today is microservices. At an architectural level, we have been moving from suites to products to services. Take the world of enterprise content management: Many now prefer to use the term “content services” as few want to buy an overarching suite; they want to pick and choose the specific services they need to meet their requirements. All in all, that’s a good thing, but it does bring with it another set of services—consulting—to try to join all the pieces together, and that is another problem. Decades of outsourcing and moving to the cloud have left many firms bereft of the skilled internal consulting services they need. Furthermore, external third-party service firms are too often overly focused on the technical elements of getting the technology up and running and have too little connection or understanding of the business challenges these technologies should improve or eradicate.
Thankfully, it’s not all doom and gloom though; more packaged technologies are coming to the market that are preconfigured and pretrained (assuming the use of machine learning) to run specific tasks. There has been recent interest in tools to help consultants (internal and external) make sense of business realities, tools to automate day-to-day task analysis, and others to mine existing business processes.
Even so, whether you call it “employee self-service,” “customer self-service,” or good old “knowledge management,” self-service is what most of these technologies ultimately deliver. The goal is to automate manual tasks and provide the right information to the right person or application at the right time. But while the technologies work well, without a thorough understanding of the current situation and a clear vision of what you want to achieve, they are useless. Even with the advantage of AI, domain knowledge and human insight are the keys to success.