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How to restructure your IT software stack to ensure knowledge flow across your business
A seamless flow of internal knowledge requires an investment in technology that is workflow-centric. In other words, a common pitfall for knowledge tools is that they sit siloed in locations that are not built to be accessed from within other common tools in the employee workflow. 

This can be remedied with software evaluation that takes into account integrations with new or existing knowledge systems. Simply procuring a wiki and hoping that it gets utilized for self-serve support is an ill-conceived plan. According to Zendesk, 91% of consumers "say they would use a knowledge base if it met their needs." The important component of this statistic is that the knowledge base must meet the user's needs. This critical detail implies that a knowledge base is useless without both the confidence that the content is accurate, and that accessing that knowledge is possible directly from within common workflows.

Consider this common example of knowledge proximity to workflow: A newly onboarded employee, thirsty for internal knowledge and unfamiliar with the inner workings of the organization, is seeking support. Often when a newly onboarded knowledge worker has questions about product, internal policy, or just requires assistance in supporting a customer query, what are the employee's next steps? Without a cultural emphasis on documentation, the employee will likely disturb others, whether in-person or through a virtual channel like Slack. With this occurring multiple times per day, for multiple employees, there is a compounding effect on lost productivity.

To avoid a series of troublesome shoulder-taps, the optimal self-serve support workflow follows what could be called the SLAT rule.

The SLAT rule is an acronym for the four key strategies required for ensuring that knowledge is organically embedded in common workflows. When restructuring your IT software stack, you should always ensure that the new products you add address these four components.

  1. Self-serve support
  2. Log the support request incident (for knowledge gaps)
  3. Author knowledge (verify, create, update, delete)
  4. Triage (via crowdsourcing, escalation, or ticket)

Slack is the perfect example of a foundational operating system for the modern workplace. It is a tool that has the capability to adhere to the SLAT rule (often natively, but otherwise with the assistance of some third-party tools) instead of just becoming another channel that hinders productivity. As Slack is a conversational tool, knowledge flows through it organically, as long as the rest of your tech stack can integrate with it. 

Let's examine the four components of the SLAT rule, within the context of the Slack example, to better explain how knowledge can integrate seamlessly with common workflows.

Self-serve Support

For Slack users, you might have noticed that the tool has usurped email as the place where internal support transactions occur. It's where questions are asked, and answers are given - sometimes more frequently than one would like.

So, it makes sense that since Slack is an essential component of the internal support workflow, it deeply integrates with existing knowledge stores so that support-seekers can search for internal knowledge directly from the place they would ask the question (like on Slack). After all, if a support seeker is going to type a question in Slack anyway, there should at least be an opportunity to query the internal wiki instead via a DM or open question in Slack. Therefore an important step in your wiki software evaluation process includes reviewing its integration with Slack or other messaging platforms.

Log the Incident

Seeking the ability to log the questions asked in your internal messaging platform is an important step in capturing data on knowledge gaps. Knowledge gaps that are found can be easily closed and eliminate future productivity blockers.

This can, of course, be done manually by counting the number of questions asked on Slack, but there are automated tools, powered by Artificial Intelligence (AI) that use Natural Language Processing (NLP) to identify and tally the data without a recurring manual effort. By introducing an NLP-powered tool that actively scans knowledge gaps, you can automate the discovery of holes in your documentation and increase overall productivity.

Author Knowledge

When knowledge gaps are identified, they can be compiled in the form of requests for knowledge from subject matter experts. Sometimes, existing knowledge is simply out of date and needs to be verified and updated for distribution in the same channels.

Since authoring knowledge can be a painstaking process, it is critical to explore options that make it as low-effort as possible to encourage ongoing maintenance of the knowledge base. In the Slack example, tools that enable authoring right within the Slack message bar can be greatly advantageous to the goal of compiling knowledge on-the-fly.

Triage

Triaging internal support issues is the exit from the self-serve support funnel. So, when existing knowledge is insufficient, you need to have a plan for what will happen to the support seeker and their issue. Ideally, your software will enable one of the following outcomes:

  • Create a support ticket
  • Crowdsource help for the individual
  • Escalate to a manager

The triaging step is a vital closing stage for the flow of knowledge through the organization. In a way, it identifies where the separation of self-serve and assisted support exists.

From a software procurement perspective, choosing software that enables these three outcomes will help ensure that the organization's flow of knowledge is complete. In the example of Slack, choosing a ticketing software that integrates with Slack where support seekers ask for help would be critical. Crowdsourcing and escalation can be achieved with third-party add-ons, as well, and may well be a component of your wiki solution.

In summary, by applying the SLAT rule to your software evaluation process, you can dramatically improve the ROI of your new software investments. Be sure to carefully consider how each new software investment complies with the SLAT rule. For those products that meet all four requirements, you can be more confident in their success after purchase.

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ABOUT THE AUTHOR

chris buttenham 

Chris Buttenham is the co-founder and CEO of Obie. Known as the "knowledge worker's secret weapon", Obie is a workflow-centric knowledge management solution that delivers fast, accurate support.

Published Thursday, April 01, 2021 7:30 AM by David Marshall
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