Earlier this month Irene Lyakovetsky, Principal of Saugatuck Worldwide and I announced digital discussions. Now we have some new discussion on my predictions for RPA and a few more goodies. We would appreciate your taking the time to watch one of the snippets if you don't have 40+ minutes for the full discussion. Please comment or suggest other interesting topics
While AI is in its spring season and is sprouting up all over and the predictions for future revenues are pretty positive, I think it’s time to try and give AI an early grade in a number of areas. I’ve picked out my top 10 categories for grading AI and have assigned a grade. In order to understand the context of the grades, I have included a difficulty score and an expected time to maturity. This is my first cut at grading AI and I’m sure I will add to the dimensions and scale over time. Let’s examine the meaning of the grade categories listed below:
AI has done well in scoped problems that are after a silo problem. This helps see clearly the results of AI even if it is a complex problem domain. Over time AI will increase its scope.
AI is often supporting a number of solutions and technology combinations through embedding itself. This brings an aura of intelligence to the solutions, so this is growing fast.
AI is good at black-box behavior by putting a buffer between the user/uses and the complexity of the problem it supports.
AI is a bit about problem-solving today rather than creation or judgment, but this is a less risky approach to establish a baseline of success.
Being able to create something or judge a situation trough iteration and inspection while including new sources of inspiration is something that AI is just starting to do.
The ability to look forward and project future expected outcomes of even plan alternative scenarios is something that is just emerging in AI.
On the Edge
AI is just starting to be distributed and being put closer to where it is needed. Distributed, just in time intelligence will grow significantly over time.
Can the application of A and it’s behavior be explained to humans or even other AI capabilities? This is a must to gather confidence in going forward. AI is headed there, but it isn’t easy yet for the most part.
Giving AI the freedom level to act alone in an unsupervised fashion is somewhat new and will require goal orientation plus constraints via guardrails for proper governance.
Integrated/Cross Context Problems
AI that senses, orients, decides, and acts across multiple problems domains and contexts is coming. For now there a few examples that have been completely successful yet. Self-driving vehicles are headed there.
AI has some growing to do before it will bloom fully. The best progress has been on focused machine learning opportunities and is quite often combined with other algorithms. Without getting into singularity issues, I think the future of AI assisting and collaborating with organizations and individuals is quite bright. I will be looking forward to the next grading period.
Earlier this month Irene Lyakovetsky, Principal of Saugatuck Worldwide and I announced digital discussions. Now we have some new discussion on my predictions for AI in 2020 and a few more goodies. We would appreciate your taking the time to watch one of the snippets if you don't have 40+ minutes for the full discussion.
James Taylor has done it again with his latest update on his decision book entitled "Digital Decisionsing". The subtitle is "Using Decision Management to Deliver Business Impact from AI". While AI is very essential in automation and extremely helpful when used properly in customer interactions, the real strategic value of AI is assisting people and organizations to make better, faster and more informed decisions.
We are early in using AI in the decision cycle for signal/pattern recognition, understanding data/decisions in multiple contexts, assisting to select the decision models/algorithms, take appropriate actions within the guard rails of goals and constraints, and learning from the decision process to become better decision-makers over time. While there are inherent risks in allowing AI to do all this in an unsupervised manner is large now, having AI assist in decision management is the prudent and successful way today. The book nicely ties the theory of decision management with real-world examples where organizations can make traction today leading them into a better decision management process in the future. Hear James Taylor describes his book in his own words.
We want to
invite you to watch our low key videos on hot topics around digital topics on a
YouTube channel called Saugatalks. Our intention is to provide you with
discussions about interesting digital topics. The first in the series is on the
top digital trends for 2020. There is a complete end to end videos on a topic
plus shorter snippets around specific topics.
Irene Lyakovetsky, Principal of Saugatuck
Worldwide, and I intend on having informal discussions around a good number
of topics related to assorted topics in and around digital technologies,
methods, and the expected business outcomes. Irene and I have worked together on
a number of panels for IBM and work well together. We are hoping that you will
enjoy the talks and give us feedback on topics that you would like to hear more
about. Please sample freely and subscribe to our YouTube channel for future
talks. If you want to read more click the show more area on the videos
It matters not if you call processes customer journeys, content workflows, BPM, cases or process flows, processes plus the resources or steps they guide/orchestrate permeate the future of organizations. Processes are everywhere in the organization and have almost always been there, so what is different in 2020? Here are my top 5 Trends
Processes are Changing Shape
Processes are becoming smaller and larger at the same time. There is a huge movement to more consumable processes in the shape of smaller focused workflows that can exist on the edge or embedded in bigger processes that may be leveraged and reused. While processes can exist in a small and effect form, they can also span a complete customer journey and be as simple or complex as you need them. In some cases, a process can represent a complete value or supply chain. They can be predetermined and modeled or they can be dynamic and goal-driven as they often are in case management situations.
Processes are Supporting Customers & Employees
Processes are often the focus of better customer experiences. There is plenty of improvement opportunities for customers in the process, but often lost in the shuffle is the employee. Customer and employee experience improvements are a great start but are not sufficient to stay competitive. To this end, organizations are looking at the complete journey even if it starts and ends outside the organization. Often organizations can compete better considering the full context of the customer/employee journey
Processes are the Hub of Automation Efforts
Since processes are often the glue that holds resources together, they are often the focal point for improvements and automation. Robotic Process Automation(RPA) focuses on task automation and have gone far with more to go. How content, process instances or work buckets flow from one step to another is a great opportunity for improvements. Work can get stuck at one point or another in a process due to a lack of resources focus or missing data or knowledge. Analyzing process instances and cases can point out automation or improvement efforts.
Processes are Getting Smarter
Processes are great for finding key hot spots for adding intelligence. It may mean making decision points in a process more capable and precise, guiding key resources in real-time to take appropriate actions or notifying managers of unexpected events, signals or patterns. Moving processes from just programmed actions to adept sensing, keen decisions, and intelligent actions is a real opportunity in 2020. This means teaming processes with strong feedback loops, machine learning, algorithms, and deep learning or additional smarts.
Processes are Becoming Transparent
Processes are often a key source of visibility for the progress of work in organizations. This means processes will be instrumented with better visualizations that can handle static and dynamic process instances and workstreams. Combined with process mining and data mining capabilities will be a key trend in 2020. Inspecting real work instance in the context of timelines, goals, and outcomes is invaluable to all kinds of improvements. Since you can only manage what you measure, process transparency is crucial.
Process in 2020 will get renewed attention as new digital technologies will be collaborating with processes especially when they support customer and employee journeys. While the process is not the most recent shiny object, it will still feed large revenue and cost improvements.