Doculabs' Insights #27
Is AI the new black? Reasons IDP implementations fail, details on our newest learning session, cybersecurity challenges, and more.
Process mining is like having a magnifying glass for your business processes.
It's a data-driven approach that allows you to visualize, analyze, and improve your workflows based on the actual data generated by your systems.
Imagine you have a map of your business operations, showing you exactly how tasks are performed, where bottlenecks occur, and how efficiently your processes are running.
Process mining extracts this information from your IT systems, such as ERP, CRM, or other software, and presents it in a clear and intuitive way. With process mining, you can identify inefficiencies, streamline operations, and make data-driven decisions to optimize your business processes.
It's like shining a light on the inner workings of your organization, enabling you to unlock insights and drive continuous improvement.
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--The Doculabs Team
From Hype Machine to Workhorse: Practical AI is the New Black
Intelligent Automation and Generative AI in the Claims Organization [NEW webinar]
Is Your Customer’s Virtual File Room Ajar?
Process Management after ChatGPT: How Generative and Predictive AI Relate to Process Mining
How to Identify Activity Effort Times in Process Mining [PM Tip of the Week]
The Growing Need for Information Literacy
6 Reasons Why IDP Implementation Fail
From Hype Machine to Workhorse: Practical AI Is the New Black
Generative AI’s supersized language models are impressive but messy. Scaling them up is a technical headache. Scaling LLMs introduces technical and ethical complexities. One primary challenge is ensuring predictable results, and then there’s the ethics of all of it. Read more.
NEW Doculabs’ Webinar – May 14
Join us for Intelligent Automation and Generative AI in the Claims Organization at 1 EDT on May 14. As your claims organizations embarks on the journey towards digital transformation, the integration of Intelligent Automation and Generative Artificial Intelligence emerges as a pivotal strategy. However, the success of these initiatives hinges on a thorough understanding of existing processes. Process and task mining offers a comprehensive approach to uncovering, analyzing, and optimizing processes within an organization. This session delves into the intersection of process mining and the implementation of intelligent automation and Generative AI. Grab your seat now.
Is Your Customer’s Virtual File Room Ajar?
Evolving regulations increasingly require companies to report on data breaches, with the draft rules issued on March 27 of this year by the US Cybersecurity and Infrastructure Security Agency representing more tightening of requirements. The article suggests three ways that SaaS vendors can help customers. Reverse the lens, and these are equally three things companies should look for in a partner. Do they:
Build cybersecurity directly into document management systems and processes?
Encourage smart security practices?
Monitor and report on evolving rules that affect you?
How to Identify Activity Effort Times in Process Mining [PM Tip of the Week]
We are often asked to determine the time various activities took. Unfortunately, many times there are not timestamps to represent when an activity started and ended. Represented as a single point in time, activities such as "Approve Invoice" lose a lot of meaning.
Our approach to building out activity effort times is to first create a list of all activities in the system in an OLAP table.
Process Management after ChatGPT: How Generative and Predictive AI Relate to Process Mining
This short article discusses the role of generative and predictive AI in the context of process management, focusing on process mining in particular. Generative and predictive AI will significantly impact process management, but dedicated process-mining approaches remain essential. Organizations need to master basic process mining techniques before advancing to more sophisticated AI and machine learning applications. As long as organizations need help finding and extracting data and have difficulties implementing obvious process improvements, it is not realistic to assume that a Large Language Model (LLM) trained on general-purpose data will be of much help. Read more.
The Growing Need for Information Literacy
AIIM’s president Tori Miller Lui puts a spotlight on this huge need. Information literacy is the understanding of the full information lifecycle and how information can be leveraged to achieve better business outcomes.
Those who are information literate understand information is a strategic asset. They also have some level of ability to identify information needs; critically evaluate the quality and integrity of information; extract useful insights; and maintain information in compliance with governance policies. Read more.
6 Reasons Why IDP Implementation Fail
Why do intelligent document processing projects fail? It’s not often due to technology. Here’s number 1: unrealistic expectations and/or lack of clear objectives. For example: accuracy rate is one of the top metrics IDP vendors will tell you about. While there are out-of-the-box accuracy levels they can guarantee for certain document types, understand that there is an accuracy floor level that you will get when you buy the software, and a ceiling you can achieve once the platform is set up to fit your specific processes and documents. Steer clear of vendors promising 100% accuracy off the bat.
Set clear objectives when it comes to the metrics you want to achieve across your document automation journey. Read the other 5 here.
EVENTS
Document Strategy Forum
May 20-22
Boston, MA
Calling all revolutionaries in the world of document and content management, customer communications, and customer experience; change is coming. Register and more info.
Just for Fun
Image credits
Open door: Photo by Dima Pechurin on Unsplash
Boy falling: Photo by Zachary Kadolph on Unsplash