I hope you and yours are safe and healthy during these pandemic days. I delivered on a promise to my Grandson and painted Kale a dragon that we kind of designed on our last visit to Austin before Christmas. It was a fun piece to do even though there is a bit of a sinister feel to it. I also completed a couple more fractals for you to see. If you are interested in seeing my portfolio or buying a piece, please click here
Today when organizations talk about content analytics, they
generally are talking about the effectiveness of marketing efforts or website
effectiveness. This is often productive but narrow leverage of content. Content
is often the forgotten large vein of big data that has more potential for
finding nuggets of business benefits. I would suggest there is a larger
category of leveraging content than content analytics applied to revenue
generation. I call this Content Intelligence.
Content Intelligence is the act of applying natural language processing (NLP),
machine learning (ML), deep learning (DL), business intelligence (BI) and
business analytics (BA) practices to a variety of
digital content. Companies use content Intelligence software
to provide visibility into the amount of content that is being
created, the nature of that content, and how it is used.
The Unprecedented Growth
of Unstructured Content:
While the has been a steady growth of traditional content
and the importance of enterprise content management (ECM), the use of this
content is being leveraged better in the new digital world. While digital
methods have increased the productivity of the first mile of content-rich process
flows, there is much more to leverage as we move to an increasingly digital
world. Organizations are looking to turn audio and video into actionable
insights in order to respond to issues in real-time, uncovering insights in
large archives, boost the leverage with machine learning ad accelerating
Utilization of Unstructured Content:
We see increased leverage of knowledge by systematically
using NLP to find key nouns, relationships, and new leverage points. Imagine
mining knowledge out of operations manuals to point to organizational knowledge
sources or to create helpful new videos for better outcomes. Organizations are
doing this right now. Imagine searching for moving images for defective parts
of managing costs and increasing employee safety. This is happening today.
Imagine equipping emergency personnel with active real-time maps of buildings
and infrastructure during emergencies like active shooter situations. This is
being done today. We are seeing the emergence of smart home and smart
infrastructures in cities leveraging audio and video. You can expect more
leverage of live and active content going forward because of the ability to
mine nouns, relationships, contexts, and interactions.
Digital Publishing is
Utilizing New Digital Assists:
Creating content is now easier by guiding authors with
better grammar, finding parallel writing that might indicate plagiarism, and
creating topical indexes for finding useful resources or references. This is
very helpful for traditional marketing and lead-generation over and above
traditional research and "publish or perish" situations. Consider
story mining of narratives to find successful approaches to creating better
While revenue generation is essential and analytics applied
to revenue efforts, content is often an underutilized pocket of big data for
organizations. We are in the early days of leveraging intelligence with various
kinds of content. There is so much more to do with content intelligence, so
it's time to increase your content IQ.
We have been hearing all kinds of data and analysis in and around the Coronavirus. In this set of sessions, we discuss the importance of setting goals before collecting and massaging data. Right now it's about not breaking the capacity of the healthcare system, but there are a number of other important things to optimize on as well. If you want to watch the full video, click here If you want smaller snippets, click on one of the topics below:
I think I speak for all who knew you. You have been greatly missed and we are all still hurting without your warm spirit. You lit up every room that you entered because of your positive spirit and attitude. People always loved when you showed up because you were so full of fun and surprises. We never knew what you would say or do, except when it came to having compassion for others. You loved hard and you were a front seat participant in life. We all miss you for sure.
You sang your way through life's trials and entertained us all. You loved "Pink" with all your being
Your beauty started in your heart and shone through often
The fun started early and you kept it going to the end
You so loved your family starting with your twin brother
The rest of the kids enjoyed your spunk as well. Nobody treated her grandparents better
While you were a storming jock that loved soccer, you cleaned up well
You loved all animals, but you had a special love for dolphins
We will all continue on without you, but we know you are watching and near. I hope you like the collage I made to hang on the wall of our home to remember you along with the pictures nearby. It's "Pink" and some pink dolphins to combine two of your many loves.
MISS YA GIRL !!!!
Family and friends in glory today especially Dad, Andy and Beth Sinur.
It appears that the days of hype-hopping for organizations
that want to make digital progress is nearing an end. The downturn that we are
facing will sober us to be diligent in what methods or technologies we chose to
reduce costs, cut time to change, and optimize revenue opportunities. It's time
to be pragmatic for the average organization and look to what popular
technologies will deliver tangible benefits quickly.
Obviously, if you are an
investor looking for new markets to make investments in, those technologies that
have the sizzle and are hot are your cup of tea. If you are an investor who
looks to ride older technologies to profit before it sunsets, your days are
going to get busier. The average organization will be looking for steady
progress towards better profitability with better customer experiences
supported by lots of cost-saving automation. This blog will identify those
newer technologies that can deliver that delicate balance.
Let’s start by looking at popular technologies by impacts
and time frames with the eye towards long term results.I've placed popular technologies on a
timeline and classified them by their biggest impact area in Figure 1. Often
these technologies start at the infrastructure level to build upon for software
vendors or organizations to build upon. When combinations of these work
together, then the packaging of development and infrastructure
technologies/methods results in business impacts.
An example would be that
Customer Excellence results in the leverage of CX, ChatBots, Omnichannel,
Journey Mining, BI, AI, Knowledge Management, CRM, Voice, Mobile, Cloud, and
APIs. Many technological influences have benefited from the evolution of
technologies over time, which you can track over the decades. Industry 4.0
would not be possible if it wasn't for bar codes, middleware, networks, DBMSs,
Process, GPS, APIs, QR Codes, IoT, Supply Chain Logistics, and Fast Data.
Figure 1 Timelines of Popular Information Technologies
While many of the established technologies have and will
continue to deliver, there is a special set of technologies that will bear the
weight of fluctuating economic and geopolitical situations. Here are my
favorites that deliver desired outcomes today and will grow well to tomorrow:
Customer Journeys for creating better customer experiences and improved touchpoints
Mining for measuring actual customer, process and resources behaviors for experience upgrades
Digital Assistants for knowledge assisted help for customers and employees
Voice / Video for making the interaction more real and possibly more entertaining
BI / AI providing analytical assists with goal-driven data/information consumption for opportunities or threats
Agile Methods for time to market delivery that leverages incremental change and adjustments
RPA for step automation of high volume, tedious, and repetitive tasks
Low-Code for time-sensitive proof of concepts, time to market delivery, and legacy replacement
Process Mining for improving processes, and locating automation opportunities
Machine Learning for identifying or automating goal, policy or rule changes
Hype hopping seems to usually only work for early investors or
organizations that are the cash cows who love to find the next big thing. The
rest of us will want sure things that deliver short term results while growing
to a longer-term set of desired outcomes. It is time to carefully map our
digital plans with a practical and experienced eye while striking a balance
between short term CPA mentality and the vision of the executive management
team. I hope the above figure 1 can help with that effort.
A special thanks to Craig Hayenga, my rocket scientist and software pro friend/neighbor who reviewed figure 1 and gave me ideas or corrections for this
We have been hearing all kinds of stories in and around AI. I have tried to gather some real-world case studies to show what works today. While AI is early in its delivery cycle, there are some encouraging and practical case studies to learn from as we build impressive outcomes with AI combined with a good number of parallel methods and technologies. Here are five pragmatic uses of AI. If you want to watch the full video, click here If you want smaller video snippets, see the list below.
In a rapidly changing
world, greater demands are put on organizations to stay agile and react
swiftly. Yet many are struggling to achieve this when using outdated tools and
techniques. Leading organizations are dramatically shrinking the time it takes
to discover and diagnose business problems, design and implement solutions and
continuously optimize processes by leveraging process modeling.
Few organizations are
as large and complex as the United Kingdom’s National Health Service. In a
recent project, Process modeling was used to help facilitate a series of future
state design workshops for mental health services in South London. This group
of hospital trusts and partnerships were competing against each other for bed
spaces across the UK. The result was juvenile patients being sent to hospitals
many hundreds of miles away from home at the very time they most needed to be
Process mapping and
analysis solutions are often used by consultancies and internal operational
teams to deliver rapid transformational change. One Solution Consultant at an
Intelligent Automation provider recently stated that “Process modeling helps us
get to 80% of the answer in a fraction of the time it used to take us. Now we
start providing value to the client right there in the very first meeting!”
Process workshops were used to challenge the teams to think about how things
worked and who was accountable for it, all captured live in a modeling
capability. This meant the participants felt they had contributed to something
tangible before they left each session. In fact the teams immediately started
putting many of these new work practices in place while still in the design
phase. The need for lengthy write-ups and analysis of workshop outputs was
almost completely eliminated. They were
literally transforming the organization at the speed of conversation.
The result of the project saw hospital stays outside the local
area drop by 75% against the baseline year. Across the partnerships, the
hospital beds total capacity used by local children increased from 52% to 90%
and there was an underspend of the budget of 12%.
While this example shows the power of live process mapping and analysis
the product also includes modules for teams that specialize in specific areas
such as; Risk Analysis, Org Design, Target Operating Models, DevOps, Lean and
Robotic Process Automation (RPA). The RPA Analysis module, for example, is used
by RPA consultancies and internal teams to build a holistic process model,
rapidly identify suitable candidates for automation and automatically generate
a business case.
In almost all cases users report a considerable reduction in the time
it takes to make key decisions and this results in higher levels of engagement
and better customer experience by leveraging process models. While this might
seem obvious, process modeling will be a key competency in transformations while seriously involved with cost savings along the way.
Often the processes, data, and cases are the benefactors of digitization. Because of this focus, digital decisions often end up being overlooked. Getting better at decisions is one of the more desired competencies organizations need. If you want the full video featuring James Taylor and me on the topic, click here. If you want smaller snippets, see the list below:
"The Geopolitics of Cybersecurity is a book that surrounds the multiple layers and dimensions of what holistic cybersecurity should look like. Not only are all the challenges laid out in detail in this book, but the possible shape of the potential journey to a balanced cybersecurity framework are explored fully. As a student of cybersecurity, I now know so much more than I imagined after reading this book. It should be in the library of all serious security professionals."
"Ron Ross has captured the essence of the rules around conjugating knowledge and properly mapping it for precision. This allows for better business communications at a minimum and leveraged knowledge at a maximum. For any organization that wants to leverage knowledge now or in the future, this book is a must-read"
There are predictions that there will be no need for artists of any kind in the future. I'm not sure about that, but what I am sure of is that AI / Algorithms are great to collaborate with to date. I am living proof that AI can assist artists of all kinds. While my love is for hand painting, my best success in the market is because of collaboration with AI. If you want to listen to the complete story of the production of art and song, click here. If you want a short on art, click here. If you want a short on music creation, click here.
One of my longest collaborations with AI: Happy Heart
With all the talk of process dying, why is "process" still in the sights of almost all of the automation efforts? Why is "process" square in the middle of better customer experiences? It's because "process" gives context for works steps necessary to attain business and customer outcomes. Here are some interesting videos that tackle the topic. You can watch the discussion from end to end by clicking here
New content on Dark Data and Dark Events for your viewing pleasure. 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. Make sure you like or follow us, please :)
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.