Illuminating the Dark Side of Transformation: Unleashing the Power of the Work Graph
24 Nov 2022
Illuminating the Dark Side of Transformation: Unleashing the Power of the Work Graph
The majority of CXOs throughout the world are concerned with increasing revenue, cutting expenses, providing excellent experiences for customers, employees, and ecosystem participants, and managing risk and compliance. Enterprises invest heavily in directing transformation programmes with the greatest personnel, supported by strong sponsorship and leadership attention, in order to meet these business imperatives.
What causes transformation efforts to fall short? Despite having several essential components in place, firms are surprised by a sizable blind spot, which is the main cause of the disappointing results. This is referred to as "the dark side of the moon."
This "dark side of the moon" what?
Because of organised interactions with systems of record (SOR) software like ERP and CRM, businesses typically have considerable visibility into how their "systems work."
Understanding the application logs that these SOR applications produce is the main method of visibility.
Businesses presume that because they are familiar with how systems operate, they are therefore familiar with how teams and processes operate. The significant blind area is located here.
People create a significant digital footprint as they use software on a daily basis. This digital footprint is likely the greatest dataset created by people to date and is about 70 times larger than the interaction data produced by all social media combined. It affects every application, team, process, and customer and is inherently complicated, undocumented, unstructured, and pervasive.
Despite accounting for 60% of where people spend their time outside of SORs, this dataset is unexplored and holds a goldmine of insights for economy business.
Enterprises may unleash enormous opportunities and increase the effectiveness of transformation initiatives with data-backed insights if they can provide structured and actionable insights from this untapped, complicated, undocumented, unstructured, and large interaction dataset.
Businesses need to "light up the dark side of the moon," but how?
One such ground-breaking innovation in the industry analysis, the work graph, which is supported by a potent graph technology, marks a paradigm shift in how businesses carry out transformation initiatives. Its effects are comparable to how Google Maps profoundly altered how people travel. With millions of nodes and edges, the work graph offers a fresh perspective on work as a map of interactions between people and software, generating insightful conclusions and facilitating action.
The work graph provides insights into how work actually gets done on the ground by showing the as-is state of processes, various ways work gets executed, the most optimal path, and common sources of friction at work within and across systems, much like how Google Maps provides visibility into the physical landscape and insights into various paths and traffic hotspots. These business world insights are a critical facilitator for constructing SOPs, RPA bots that automatically generate realistic automation pipelines, aiding in the creation of training and onboarding strategies, and delivering real-time nudges when users stray.
How do graphs assist businesses in achieving their goals?
The work graph is essential for expediting transformation programmes and fostering continuous improvement within companies as the digital footprint left by users expands. The following are some ways that the work graph supports successful transformation outcomes:
Places human–software interactions at the heart of change: Large businesses use a variety of tools and apps, which results in a fragmented landscape where systems don't communicate with one another. According to a survey, the typical user switches between 22 applications 3600 times every day to get their work done. Enterprises typically try to fix this issue by adding personnel to serve as "glue" or "middleware" to connect data context between apps but the underlying problem is not addressed.
From the perspective of the "users," streamlines procedures. Let's use the following case to demonstrate: The biggest difficulty with automation today is not "how to automate," despite the promise of RPA as a tool for optimising procedures.
Analysts believe that around 50% of RPA licences in businesses are not being used because of the question of "what to automate."
Businesses need a solid grasp of the dataset of human-software interaction recorded by the work graph. In addition, students must comprehend the activities, flows, variations, effort, setting, and impact. Enterprises require user-perspective insights in order to create a reliable automation pipeline.
Inadequate privacy protection: Rude technology, such computer-vision-based user activity recording, poses serious privacy problems in the market analysis. The typical process intelligence technologies that surface personal information about people should be avoided, according to a Deloitte survey on intelligent automation. The enterprise's stance on privacy is made clearer by the work graph: maintaining each person's privacy while exposing teamwork patterns is a core, non-negotiable principle.
Conclusion: Getting going
Companies in the news from many industries can switch over to the work graph with ease. Moving to the work graph does not require extensive background research. One major benefit is that it requires no IT integration, thus it may be implemented without any disruption or revamp. The time value is yet another plus.