End user computing is a direct result of the age-old frustration of waiting, but doing this correctly has the potential for many pitfalls. Everyone has had to wait on something at some point in their life: whether it was as innocuous as waiting for the kids to be ready for school or a spouse before date night, as frustrating as the line at your favorite coffee shop or checking out at the grocery, or life threatening as for an arriving ambulance or organ donor availability.
In business, wait times can mean the difference between customer loyalty and loss, productivity and profitability, or competitive differentiation and obscurity. While a lot of attention is given to average wait times for customer service, very little is often observed (or managed) for internal IT requests from line of business leaders. This gives rise to shadow IT projects where industrious executives decide to bypass this queue and solve their technology request on their own. While the promise of end user computing certainly justifies the project, it will be the execution that determines whether or not the “juice was worth the squeeze”. Success can only be achieved by getting past current technical debt, understanding the nuances of the intersection of end user computing with GenAI and developing the right partnerships with teams experienced in delivery and timely ROI.
It is not that technical departments don’t want to improve their response rates to line of business executives. They are unfortunately mired in technical debt which usually takes priority over new items that the business side of the house may deem as necessary for staying productive, profitable and/or competitive.
Recent McKinsey & Company research reported that 40% of the average technology portfolio is dedicated to account for technical debt and at least 20% of the technical budget dedicated to new products is diverted to resolving issues related to that technical debt. As you can imagine, additional costs incurred by technical debt shows itself when an organization also has to contend with other hard costs such as the cost of SaaS licenses hiding in line-of-business budgets from shadow IT projects.
In order to deal with this technical debt and reduce, if not eliminate, wait times for line of business technical requests, many companies are, unfortunately, allowing an end user computing model to creep back into the organization. Put simply, this is a platform with associated processes and policies that allows nontechnical users the ability to create, manage and use their own business applications to address their own needs more rapidly. As you can image, there is a right way and a wrong way to make this happen. The wrong way can mean chaos if end users go back to shadow IT practices and unreliable (read now governed) tools.
Thanks to innovations in generative AI (GenAI) and new machine language techniques such as reinforcement learning, end user computing is more than just a desire, but an actual technical reality if done the right way. Three core elements must be accounted for to ensure your end user computing approach will help instead of harm your organization include:
Mitigating these risks of successfully implementing an end user computing platform should not be an exercise in futility in and of itself. This is where an intelligent cloud can step in and provide the end user computing platform you seek.
So how does an organization eliminate the threat of shadow IT projects, reduce technical debt and satisfy line of business user requests in a timelier fashion by implementing an end user computing model?
The answer is actually easier to implement than you may think. Emerging open source, no-code intelligent cloud solutions like UBIX can deliver on the promise of an enterprise data intelligence platform and end user computing to supercharge the quality of reporting and analysis with a decision intelligent cloud. By consuming all on-premise infrastructure, cloud-based infrastructure and cloud application datasets directly, UBIX makes the integration seamless and ensures that your existing data assets are fully utilized by LOB with a simple natural language query. This also frees data scientists and data analysts to address innovations instead of generating more superfluous reports.
Realizing the promise of End User Computing starts with an understanding of the realities (as opposed to the hype) of emerging GenAI with a decision intelligent cloud and how a no code solution can deliver on the promise of bridging the communication gap between the average business executive and the average technical/IT resource has never been easier. Download our free eBook titled “Solving the Problem of Data and Decision Making” to help better understand the details of emerging AI concepts and how to ensure digital transformation and business-led AI success. Or if you can spare 22 minutes for a mini–2025 End User Computing Workshop, you can contact one of our experts today.