As companies evolve through the various stages of growth, their needs change from a knowledge management perspective as well. If you’re not modernizing your knowledge management strategy to adapt to the demands of growth, you are missing out on opportunities to improve productivity and get the most return on the internal knowledge your company has cultivated along its journey.
In startup-land, chaos is the norm. It’s the founder’s job to control the internal entropy of the organization and keep the team on the path of proving a hypothesis and hopefully build a company from there. Startups are sponges for knowledge. Their entire purpose is to acquire knowledge about a market quickly and then deliver a product that solves a need.
Because startup employees are free from corporate bureaucracy, they can test out new technology (such as micro-SaaS productivity apps) freely. While this is great for improving productivity, it also adds to the chaos and confusion of where correct answers lie within the organization.
Common internal challenges
- Multiple information silos, often with poor organization
- Onboarding new team members without a codified onboarding process
- A need to begin building a common body of knowledge on many topics and make it accessible in the flow of work
- Limited financial resources (not enough revenue to support operations)
- Limited time (financial runway does not provide unlimited time to solve the product-market-fit problem)
Because chaos creates confusion, a startup’s best strategy is to consolidate access of knowledge to a single source of truth. While dumping all files into one or more repositories (like Google Drive) is convenient, it doesn’t scale well. Saving all files into a repository doesn’t identify which document or file contains the correct knowledge and it potentially leads support seekers down the wrong path.
Founders that want to retain rigor in their strategy will recognize that the earlier that you establish your first company wiki, the better. Investing in a central knowledge platform helps shape the culture around documentation and prepares young companies to scale properly.
Scaleups are companies that have showed some promise and identified product-market-fit. They are still at the stage of burning cash because they are rarely cash flow positive at this stage. Scaleups are still at significant risk of failure because there is a delicate balance between overspending to achieve a stable status and not spending and enough to reach growth goals.
The distinct problem that scaleups have that startups do not, is that they have figured out that customers will pay them for something, but they need to figure out a repeatable strategy that will bring them to “cash-flow-positive.” Typically the way to achieve this is through adding headcount – often through client-facing roles like Sales, Customer Support, and some Operations roles. This has implications on knowledge management because onboarding employees requires training, and in the case of a scaleup, time and resources are still limited.
Common organizational challenges
- Onboarding new team members in large groups simultaneously
- Increased dependency on documentation to support onboarding
- Frequently repeated questions arise from both customers and internal teams
Preparing for mass-onboarding involved creating a replicable onboarding process that emphasizes self-serve support. This will minimize disruption to tenured employees. Explore solutions for capturing and sharing answers to frequently asked questions, which are bound to occur with groups of new employees seeking the same information simultaneously. There are numerous software solutions that aim to directly solve the FAQ problem – find the one that fits best into your specific workflows.
Congratulations! You’re working in a stable company. Worrying about bankruptcy caused by a cash-flow crunch is a thing of the distant past, and now you’re trying to make sure everyone is getting along and everything runs smoothly and predictably. This often involves streamlining to shed some of the unnecessary costs created by the scaleup stage and trim down to the company size and trajectory that is manageable.
Because tools and processes are often disparate, support-seeking employees can avoid established protocols and just choose the path of lowest resistance. Unfortunately, this means that they often abandon self-serve support channels. Consider the operating systems in which people work and communicate, such as Slack or Microsoft Office/Teams. These are the places where questions are asked and knowledge is shared. So when an employee has a problem, instead of creating a support ticket through an existing channel, instead they just ask for support through Slack. This shoulder-tapping relieves them of their duty but creates more work for the support team.
Common organizational challenges
- Employees not following processes because of distance from workflow
- Abandoning self-serve support channels because it’s just easier to ask the rest of the team for help
- A need to consolidate knowledge silos to limit confusion for internal support
Explore technologies that layer productivity into existing processes instead of completely overhauling the things that have already been established. For example, if you have a support ticketing solution in place, but people continue to ask for support in Slack, instead of sourcing a new ticketing software, look for a solution that brings your existing ticketing solution to Slack.
Maximizing enterprise profitability typically involves optimizing efficiency. With, potentially, many thousands of employees, they can increase profitability through automation because of the sheer volume of data and frequency of recurring patterns. At such a high throughput, the multiplier effect created by recurring problems at the enterprise stage can erode the bottom line quickly. Many “stable company” stage organizations feel that they have this problem, but often they often underestimate the relative frequency of recurring issues.
Automation can have a profound impact on managing organizational knowledge at an enterprise scale. Because of their size, enterprises encounter frequent low-value challenges that are best solved by automated solutions rather than dedicated employees.
Common organizational challenges
- Unmanageably high frequency of low-value support issues
- Reluctance or inability to shift technology due to, high training costs and slow procurement processes
If ever there were an opportunity to take advantage of an AI-powered solution, the enterprise company stage is it. These companies certainly have the volume of issues to justify the investment and the training data to provide meaningful results. For example, using technologies that employ Natural Language Processing (NLP), you can extract language patterns from the places where conversations happen (eg. Slack) and use AI to match them with organizational knowledge to automatically resolve the lowest value, most frequently recurring problems.