“… It's very clear
Our love is here to stay
Not for a year
But ever and a day”
Whether it’s a great love story or frenemies, the relationship between technology and support functions like process and knowledge management is here to stay. A great process improvement and knowledge management toolkit includes storytelling with data, ways to connect with disperse project teams, and the ability to make work easier.
The growing integration of technology and process and knowledge workers have become even more emphasized in APQC’s most recent priorities surveys. Almost half of the process teams provide direct support for their organizations’ technology implementations—ranging from large-scale, legacy replacements like ERP systems to smaller automation projects. Knowledge management teams are tapped to support their organizations’ digital transformation and intelligent enterprise efforts, and process and knowledge management teams are supporting technology implementations and embedding technologies into their toolkits.
The three key technologies that both groups have adopted: are data visualization, automation, and collaboration tools.
In addition to recent research on the topic, I also got a chance to talk to Margo Rose, senior director of enterprise lean value delivery at the Federal Home Loan Bank of San Francisco, and David Meza, senior data scientist at NASA, about their use of data visualization tools and automation. Both of whom are speakers for the Technology in Context track at APQC's 2022 Process and Knowledge Management Conference, taking place May 11–12 in Houston.
These are tools that create a graphical representation of information or data and develop graphic elements for reports or dashboards. Data visualization tools help ensure decision-makers can access information and make better decisions by converting massive amounts of information and complex analysis into visuals.
Though data visualization tools are nothing new, they can help drive data-based decision-making now more than ever by converting data and information into easy-to-absorb forms—which enables better pattern recognition and insights.
Take graph databases for example. According to David Meza, “This technology allows us to see data uniquely compared to traditional databases. It allows us to look at relationships across data a lot easier, which helps us find clusters and patterns in the latent information within our data. The graph algorithms, then, help us speed up the process of finding that data in ways we haven’t been able to do in the past.”
Additionally, data visualization tools like dashboards, put information into decision-makers' hands at the “right” time so they can analyze improvement opportunities and projects through a lens of objectivity.
According to Margo Rose, automation is “a new-ish technology. Although it’s s been around for over a decade, most organizations are still trying to figure out the best ways to utilize and incorporate it and how to get an RPA program off the ground.”
At its core, automation is the use of software to mimic human action and connect multiple, fragmented systems together. Process automation enables systems to carry out high-volume, multistep actions— without manual intervention by employees—to capture information, manipulate data, or trigger responses in other systems. Process automation helps organizations improve cycle time, increase capacity, reduce errors, and minimize FTE hours spent on transactional or low-value processes. Automation work is typically found at the heart of most digital work.
For Margo Rose, “the best impact is that RPA is getting team members re-engaged with their routine and standard work. And that means not only looking for ways to eliminate manual tasks but also understanding the work itself in more depth.”
The final common technology, collaboration tools, has always been vital for dispersing teams working across geographies, and they have become increasingly important over the last few years. In their simplest form, collaboration tools help two or more people work together on a shared task, project, or goal.
With virtual work environments becoming more common, collaboration between a dispersed workforce requires adopting tools that help teams communicate and work on documents and projects in real-time. Where organizations tend to struggle is finding virtual collaboration tools and practices to support complex collaborations around innovation, team building, and change management.
Better in Combination
In addition to the intrinsic value of each of these key technologies, mature organizations understand optimization comes when through mutual support. When asked about the next stage of technologies in their organizations’ both Meza and Rose cited one another’s technologies.
David Meza would “like to see technologies incorporated like RPA and chatbots to automate some of the things that our employees may be searching for within our database. For example, when they’re looking for a detailed opportunity, we could automate that and have it be more of a push than a pull. Something would just pop up that meets their criteria.”
While Margo Rose would “love for our next stage of development to be graph databases. That’s exactly what I want to be doing.”
For more information on this topic check out From Graph Algorithms to Process Automation: Tools for Success or join Margo Rose, David Meza, and other process management experts to learn about how they use core technologies in their process and knowledge work at APQC's 2022 Process and Knowledge Management Conference, taking place May 11–12 in Houston.