What do we mean by technical debt in the context of workload automation? It’s an accumulation of quick fix workarounds that build up as a result of the limitations of old and out-of-date legacy scheduling or workload automation tools. These workarounds are called “debt” because they’re compromises that add an ongoing and future burden to the organization that can only be repaid by extra work.
Technical debt costs a huge amount of manual effort and time as your best team members become firefighters, constantly checking that processes complete, infrastructure is running, and patches are made. Legacy tools just don’t allow for business logic that reduces the need for human intervention by enabling processes to automatically adapt to different variables.
And with older schedulers, business operations staff can’t really know what’s happening with their processes. This may seem unimportant, as long as they get the results they need. However, when something goes wrong, it creates a mystery that takes more time to solve.
For example, many legacy schedulers simply can’t tell if there are problems hidden within data files. Typically, they just indicate what files have moved or been updated—not what’s going on within them.
This can cause big problems for many common complex activities, such as those that support business intelligence (BI). Without some visibility into the data itself, users only find the problem once they get inaccurate BI information—and that’s too late.
Modern digital business automation can verify whether something is missing, or a file is too large or small – and let the organization know straight away. There is no need to spend additional time manually checking that all BI files are correct or complete.
To get this functionality with older, disjointed schedulers, operations experts often have to create additional jobs to check file data before it goes across to the BI application. Once again, this becomes technical debt that adds cost and complexity over time.
A better solution is to use modern workload automation technology to build automated runbooks, which provide guidance when processes encounter unusual situations. By adding unique business logic to processes, modern workload automation enables auto-remediation, so processes keep running rather than halting or having to restart.
If, for example a data file is smaller than it should be, the system can automatically pause the process, change settings and take an alternative path to complete the process – without manual intervention. Add this and other common remediation steps to your runbook using agile workload automation and you have a way to cut complexity and manual effort while increasing speed and accuracy that improves over time.
RunMyJobs by Redwood® is designed to help you build exactly this kind of operations scenario. It’s the fastest way to wipe out—and stop accumulating—technical debt in your daily jobs.
Find out more about RunMyJobs®, the world’s only enterprise workload automation as a service solution, and sign up for a free trial, here.
About The Author
Devin Gharibian-Saki brings a wealth of knowledge and expertise on enterprise IT, the SAP ecosystem and business process automation to his current role as SVP of Business Development and Strategy at Redwood Software. Experience within product marketing, product management and enterprise software sales enables Devin to drive strategic initiatives and alliances for the organization and unlock new business models and go-to-market strategies. Acting as an executive advocate for the customer, Devin is passionate about delivering the best solutions to make the most out of a customer’s environment. His approach centers on connecting with customers, prospects and partners to better understand how Redwood can help their digital transformation initiatives, improving their automation roadmaps by leveraging a combination of his SAP and process optimization proficiencies.
Prior to working for Redwood, Devin was an SAP Technology Consultant, working directly at SAP and at EnBW, the 3rd latest utility in Germany. Devin holds a diploma in Mathematics from Karlsruhe Institute of Technology in Karlsruhe, Germany and as well as two patents.