Archive for the ‘VIP’ Category

What’s Next in Hardware

July 16, 2021

What’s Next in Hardware

FountainBlue’s July 16 VIP Roundtable was on the topic of ‘What’s Next in Hardware’, with our hosts at Renesas. Although our executives in attendance represented a wide range of roles, organizations and industries, they all agreed on the following:

  • Hardware innovation has been accelerating as the pendulum swings back to the need for hardware to support the rampant innovations on the software side.
  • Use cases abound for both enterprises and for consumers. The trick is to drill down on a particular use case and address a problem which the market would fund.
  • The form factor must be smaller, while the functionality must be broader and more versatile. 
  • Digital, analog and power solutions will be integrated and optimized as we continue to innovate.

A key to effective hardware innovation is balancing privacy, security and access. Just as it’s impractical to design a house without windows or doors, we can’t design solutions which are absolutely secure with the utmost protections of our privacy while providing optimized access only to the approved parties all the time, every time.
Another key is the need to focus on real problems which need to be addressed, particularly when decisions need to be made quickly, when lives are at stake. Whether we quickly get more hardware at the edge, integrating with more distributed cloud solutions, or whether we leverage hardware to be more efficient and effective at work, more immersed and involved in life, the truth is that hardware innovations in the next few years will continue to be revolutionary and transformational.
Below are some highlighted opportunities for hardware innovation mentioned by our executives in attendance.
Edge Computing

  • Optimizing hardware solutions on the edge so that processing is more efficient and effective;
  • Designing wireless solutions which provide faster end points;
  • Providing drones to collect data such as gas leaks; 

Energy Management

  • Proactively managing energy efficiency and renewables at data centers and complex end points;
  • Providing low-power, hardware-driven connectivity for enterprise and consumer usage;

Sensing

  • Leveraging hardware to sense everything from light to heat to sound;
  • Designing augmented reality solutions for enterprise and consumer usage;
  • Replicating human senses such as smell and taste;

Integration Challenges and Opportunities

  • Reducing the weight and size of hardware, so that it can be more easily integrated into solutions;
  • Utilizing AI and ML to optimize custom hardware design so we can optimize durability, usefulness and manage risk and wear and tear; 
  • Replacing human functions with hardware and prosthetics;
  • Supporting the growth of the equipment-to-equipment, equipment-to-cell-tower 5G network; 
  • Stretching the capacity in memory so that we can process more information more efficiently; 
  • Offering Confidential computing solutions, embracing hardware as part of the security strategy.

The bottom line is that hardware innovation is a work in progress, with much at stake, as hardware continues to make software smarter. And it’s not just about the technology, just the hardware and software. It’s also about collaborations across organizations and policies and compliance requirements.Although the conversation this morning was eerily futuristic, it was also at the same time utterly real, and absolutely practical and prophetic, exciting and daunting at the same time. 

The Future of Work

June 11, 2021

FountainBlue’s June 11 VIP Roundtable was on the topic of ‘The Future of Work’, with our hosts at CITRIX. As usual, our participating executives represented a wide breadth of backgrounds and perspectives. We are all in agreement on the following:

The future of work was very much impacted by the pandemic for all participating executives, and everyone is scrambling to plan-fully and proactively address the current, projected and future needs of our workers, partners and customers. We don’t know what the future will hold, but we do know that leadership and communication will help us collaboratively design solutions which benefit all, and that iterating on the adopted strategies and plans will help us more progressively serve everyone.


Companies large and small of all ilks and industries have adopted the technologies, processes, support and resources to ensure that most of us are able to work harder and more productively now than ever – even though we are restricted from interactions and travel.We don’t know what the future will hold, but we do know that the productivity levels are not sustainable in the long term, as it will lead to burn-out and attrition.

  • We are all at various levels of returning to a hybrid form of work, and are all plan-fully considering who returns to the office and how the return will most productively benefit everyone.
    • We don’t know when and where this return will happen, but we do know that we need to proactively address, manage, and communicate the logistical, policy, infrastructure, safety, and other issues introduced by the return-to-work, and get buy-in and support for any return-to-work plan.
  • We all agreed that technology has been progressively and aggressively adopted to help us all work through the pandemic. But we also agree that no technology will ever replace the need for workers.
    • We know that we will always have both workers and technologies, but we aren’t sure how to best optimize each as we return to work. The plan will morph and flow over time as the technologies and the workers both become more integrated and more sophisticated.
  • We all agreed that this year-plus of working from home helped us all better connect with ourselves, our family, with nature, with our purpose. We all know that this will forever change the way we look at our work, and the choices and sacrifices we make for our work.
    • As leaders, we need to understand the motivations of our people, and ensure that we can speak to the purpose of why we do what we do, and how we add value to our team, our company, our customers, our future, our customers. 
  • We all experienced how the pandemic made us feel both so isolated and yet so commonly human. As we return to work, we are all strategizing on how we can feel more deeply connected with each other so that we can better serve each other. 
    • Work leaders need to facilitate that communication to drive that connection between team members and company leaders at all levels.
  • The topic of privacy, security and access was prominent prior to the pandemic, and will become even more as we return to that next normal. 
    • Proactively managing that balance as we enter the next normal will remain an ongoing challenge.


Below is advice on how we can better do any of the above.

  • Take advantage of opportunities to have serendipitous discussions with your team, your partners and your customers. Building deeper relationships beyond work will not only help you with your work, it will also help you be more happy, more human.
  • Look for opportunities to manage beyond the silos of groups, apps or organizations. There will be many bleed-overs of each as everything becomes more integrated, more complex.
  • Choose and adopt best practices for the good work you do. Celebrate victories and successes and learn from each.
  • Be proactively protective of your mental health, your personal time, and encourage your others to do the same.
  • Build ecosystems and relationships which will support you personally as you grow and develop.
  • Be flexible about what you expect and how you and others respond to what they experience.

The bottom line is that we can all see the opportunities in the challenges, be more confident despite the fear, when we look at the future of work, if we continue to focus on leadership and innovation goals.

AgTech and FoodTech Innovations

May 14, 2021

FountainBlue’s May 14 VIP Roundtable was on the topic of ‘AgTech and FoodTech Innovations’, with our hosts at Honda. As usual, our participating executives represented a wide breadth of backgrounds and perspectives. The biggest takeaways are around the range of innovations for agtech and foodtech. Technology is weaving its way into this slow-adopting industry.

  • Mobility and robotics solutions are doing everything from improving our supply chain to processing more efficiently, to managing the integrity of our production and manufacturing.
  • Planes and drones are collecting the images and other data we need to proactively manage the way we plant, produce, harvest, and distribute better quality crops and higher yields of crops.
  • AI and ML solutions are helping us optimize seeds, plants, crops as well as livestock.
  • Food science and agtech is helping develop quality protein from plants and even from microorganisms.
  • SaaS and digitalization solutions are helping manage things like crop health and food wastage – connecting a wide range of siloed stakeholders. 
  • End-to-end crop optimization solutions coupled with strategic partnerships in densely populated regions will help get quality food into the hands of hungry people in population-dense areas.
  • Food science solutions will help fortify the crops we produce, optimize seeds so that are more productive and nutritious, and help feed more people with fewer resources.
  • Proactively managing food production based on projected needs will help everyone across the ecosystem optimize distribution and minimize waste.
  • Understanding the taste and quality of a seed and a plant before it is reaped helps farmers plan their planting and pricing while helping markets influence availability based on preferences.

We have come a long way, but there are still innovation opportunities ahead. It’s clear that our executives in attendance will continue to excel at leveraging their diverse experience to transform industries, provide value, while collaborating to amplify impact.

Leading Industry 4.0

April 9, 2021

FountainBlue’s April 9 VIP Roundtable was on the topic of ‘Leading Industry 4.0’. As usual, our participating executives represented a wide breadth of backgrounds and perspectives. The conversation focused not just on the supply chain, process improvement, automation and robotics which are typical for Industry 4.0 discussion, but also focused on the data management and strategy around it.The first comments are of course about the increasingly larger volumes of data and the increased pressure to respond more quickly and more strategically based on that data. Below are some best practices on how to successfully manage that data.

  • Collect data for strategic reasons, focused around corporate goals, around customer current and anticipated needs, market trends.
  • Create and reinforce a culture where data share and best practice sharing is the norm, where everyone helps everyone else solve problems and make decisions.
  • Share your data and your learnings with other products, other divisions, other organizations, etc., but use your best judgment to ensure that you maintain a competitive advantage and are engaged in win-win collaborations.
  • Analyze the data anomalies as they may point to opportunities or current or pending challenges.
  • Move from Reactive to Proactive mode, going beyond generating and reporting on data, but looking beyond and beneath that to address questions such as
    • what are the data trends
    • what are the implications based on data
    • what are the underlying causes for the data
    • what kinds of decisions should we make based on data

Below are additional best practices for managing Industry 4.0.

  • Add value across the value chain within and across companies, products, roles and geographies. The more of the right partners and leaders participate, the more value for all. 
  • Focus on both the performance of the hardware/software/solution while also ensure that the user interface is intuitive and meets the preferences and needs of the targeted profile audience.
  • The more energy and power you can channel the better, within reason, but make sure that you’re focused on solving the problem and creating the solution which fits your corporate goals and your customers’ needs.
  • Think ahead at all the things which might impact how you can custom-design, create, distribute, manage, support, etc., your solutions to manage the ripple effect. We all learned the lesson about the well during the pandemic 
  • Look not just at the data generated real-time today, but also at the decades of data we’ve amassed to help us better manage the needs of others.
  • With that said, the need for privacy, security and access is of primary concern. No solution is complete and effective without folding in these elements.
  • Look not just at how products are manufactured, but look also at how the innovations around Industry 4.0 will help leaders from all industries better deliver exceptional value to their very demanding customers. 
  • Leverage the latest technologies to keep current, realizing the impact of Industry 4.0 advantages, including Digital Twin and 3D Printing, data analytics, robotic automation, etc.,

Industry 4.0 is in its infancy, as we work to be more efficient while being more excellent, leveraging technology and collaboration. The challenge has been how to vacillate between looking at the strategy and big picture while also focusing on the weeds of the data, the details of the process, the needs of the individual customers and each individual person involved in delivering customized solutions for these customers. 

Resource: https://www.mckinsey.com/featured-insights/americas/building-a-more-competitive-us-manufacturing-sector 

Innovating on the Edge

March 12, 2021

Innovating on the Edge

FountainBlue’s March 12 VIP Roundtable on the ‘Innovating on the Edge’ topic included executives representing a wide breadth of backgrounds and perspectives. We began with some definitions about the ‘Edge’. In the ‘old days’, the Edge might be defined by where the wires end – at the point of going wireless. But today, most things are not hard-wired, and we look more at the edge of the cloud – where the cloud meets the sensors and devices.Our executives agree that it’s becoming increasingly more important to innovate and manage on the edge, but there are many business and logistical challenges for doing this well. 

  • Data Challenges: The volume of data generated by devices on the edge is immense and the challenges are varied.
  • Relevancy: getting filtered and relevant data to the right reports and programs
  • Latency: the time it takes to get the data to the right report and programs
  • Movement: moving data from the edge to other areas in the network and in the cloud can be complicated and takes time
  • Storage: management and maintenance of current and past data can be complicated and expensive

Problems beyond the data include:

  • Computational Issues: programs processing of the volumes of data to understand what’s relevant, what the implications are
  • Outdated and Sub-optimal Programs: legacy applications and other programs on enterprise networks may not be as effective and may even pose security challenges and additional expenses
  • Communicating between moving entities: car-to-car, car-to-object, car-to-people communication has its unique challenges which require collaboration between many stakeholders – from cities to auto dealers, from government officials to 5G developers, from business leaders to consumers
  • Infrastructure and Policy Challenges: we need the policies, support and funding so that we can invest in infrastructure upgrades which further allow for innovating on the edge

Below are best practices for innovating on the edge.

  • Practice Data Gravity, which treats data at its origination site, rather than moving it to another location before working with it. This addresses the data issues around latency, storage and movement.
  • When filtering for relevant data on the edge, the algorithms don’t need to be that precise, just identifying data that’s in the right ballpark.
  • Invest in solutions which minimize latency, especially when lives are at stake –  for example for healthcare and automotive solutions.
  • Design smaller form factors but with more functionality and more control.
  • Get immediate, deep and broad visibility on security exposure and breaches.
  • Create and join partnerships with carriers, vendors, providers, regulators to support the infrastructure needed to innovate on the edge.
  • Look to the AI for the historical trends and integrate that into your solution,  while also looking at Machine Learning to make predictions based on past behaviors and information.
  • Optimize for tiny computers on the Edge, which can do much more processing more quickly. 
  • Design more sophisticated environmental sensors which would give real-time feedback, monitoring for specific issues. 
  • Pay close attention to the user experience – what’s intended and what’s experienced. 

The bottom line is that we will all continue to innovate on the edge, and companies and consumers will continue to reap the benefits of it in our day-to-day lives. 
Resource: March 8, 2021: Global Mission Critical Communications Market Report 2021: AI-powered IoT Critical Communication Market in Public Safety will Surpass $20 Billion by 2028 https://www.prnewswire.com/news-releases/global-mission-critical-communications-market-report-2021-ai-powered-iot-critical-communication-market-in-public-safety-will-surpass-20-billion-by-2028-301242381.html

Bigger Solutions with Smaller Devices

February 12, 2021

FountainBlue’s February 12 VIP Roundtable on the ‘Bigger Solutions with Smaller Devices’ topic included executives representing a wide breadth of backgrounds and perspectives, but they agreed on many things.

  • Hardware will continue to become smaller while gathering a wider assortment and larger amount of data real-time. Software will become bigger to optimize functionality and performance around the data and ensure its ongoing usefulness for all stakeholders.
  • The Future of Work will be remote, and hardware and software options need to fit the functionality, accessibility and security requirements of the (internal and external) customers. 
  • Optimizing managed services will help enterprise IT departments focus on the employee needs and the employee experience, rather than on the infrastructure functionality like privacy, security and access.
  • Enterprises need to proactively update and integrate all in-house and partner solutions, especially legacy solutions, to ensure their ongoing usability, performance and security. Reactively responding to issues could waste a lot of time and money and reflect poorly on the corporate brand.
  • Enterprise and government infrastructure must be enablers of the hardware and software functionality adopted by staff and citizens, and this infrastructure must be upgraded to meet the ongoing needs of these customers.
  • The functionality will expand with the demands of the customers, demands of the market. Form factors such as the body or a car offer guardrails for the range of solutions created – they must fit the user/target! But the connectedness between the solutions and the functions themselves can be more adaptable and fluid. 
  • Solutions may become much more complex, but users still want the solutions to be easy to use and customers expect a great immersive experience.

Below are some opportunities in this space.

  • As we provide more software functionality into smaller form factors, the phone and other ubiquitous devices must provide even greater functionality – including healthcare monitoring applications, decision-making of real-world devices and equipment based on real-time reporting, and other functionality. This is particularly true with the roll-out of 5G.
  • There will be an increasingly HUGE appetite for optimized hardware and software solutions which are high-performing, scalable, true-to-spec, and even self-monitoring/self-correcting. 
  • We will all continue to develop hardware solutions which are flexible, small and sleek, with a shape and size that would fit the target destination. 
  • Individual hardware solutions will be integrated with multiple software solutions to optimize functionality, usability, and form factor. 

The bottom line is that the hardware will get smaller, the software will get more integrated, more scalable, more versatile.

Data Meets Healthcare

January 15, 2021

FountainBlue’s January 15 VIP Roundtable on the ‘Data Meets Healthcare’ topic included executives representing a wide breadth healthcare industries – from pharma to biotech, from healthcare services to digital health, and even tech companies in semiconductor and consumer electronics had perspectives on the topic. We all agreed that the advances in technology and in healthcare have facilitated the amazing response to a worldwide pandemic and other pervasive and emerging health issues.Although their backgrounds and strategies varied, our participating executives agreed on the following regarding data meeting healthcare.

  1. Data will continue to be pervasive and overwhelmingly available. And the challenge will continue to be in selecting the relevant, true and actionable data which would best serve stakeholders across the ecosystem, which protecting their privacy, and providing selective and immediate access.
  2. Focusing on getting the data right alone can help improve how quickly and accurately we diagnose, treat and care for our patients. Indeed, it could also help prevent diseases and conditions and help mitigate risks.
  3. There may be opportunities to extrapolate from large volumes of data to draw conclusions and help develop initial diagnosis and treatment strategies.
  4. Proactively managing the usage of equipment and materials and pharmaceuticals with data will help ensure logistical and operational excellence in support of the healthcare needs of our patients, and the bottom line of the providers and caretakers across the ecosystem.
  5. The more data we gather about people with similar conditions, the more we learn about each individual person, and the more generalities we might be able to make about a particular disease. But every person will respond differently to different things, so respect the collected data without making direct correlations and conclusions on how any one person might react and respond to any particular scenario.

We all remarked on the value of collaboration across the ecosystem so that we can all better benefit. Below is a compilation of thoughts on the market opportunities ahead, which might benefit from collaboration.

  • Personalized medicine can be a real opportunity if we can overcome the privacy, security and access challenges and if the technology continues to evolve so that we can design custom diagnosis and treatment for patients.
  • Empowering the consumer with data will help them as patients better partner with others across the ecosystem to make better decisions in researching their own conditions, and also in making treatment and care decisions.
  • Identifying and treating a niche market may have ripple effects in supporting others. The example of an expectant mother comes to mind.

Throughout the discussion, there was a message of hope as we all grapple with the different challenges and opportunities offered as data meets healthcare. It’s significant that companies far outside the healthcare sector are looking closely at how data meets healthcare, and what the business and market  opportunities are, and also significant that each executive is exploring how we can better connect and provide more impact for all.
Please also see Frost & Sullivan’s Top 10 predictions for healthcare in 2021.

Smart Cities, Smart Buildings

December 11, 2020
FountainBlue’s December 11 VIP roundtable : ‘Smart Cities, Smart Buildings’

FountainBlue’s December 11 VIP roundtable was on the topic of ‘Smart Cities, Smart Buildings’, conducted online with introductory remarks provided by our host company at Amazon. Below are notes from the conversation.

Today’s participating executives represented a wide breadth of industries and roles, across the spectrum of technology – from semiconductors to fabs to end consumers. Each brought an interesting perspective about the opportunities for smart buildings and smart cities.  

We launched the discussion talking about the technology innovation explosion around semiconductors, networking, storage, software (AI, Advanced AI, ML) which facilitates the adoption of Smart Building/Smart City solutions. The pandemic and its implications are also accelerating the development and adoption of technology.  

  • Whether it’s on the edge, in the fog or in the cloud, it’s always about the data. But we need to make sure that data is relevant, timely, filtered, and targeted in its delivery in order to provide maximum benefit for all stakeholders, with actionable recommendations based on pre-defined requirements and parameters.
  • Balancing privacy, security and access remains of paramount concern. Individuals, cities, countries, companies will differ in terms of their sensitivity levels and options for managing these elements, but each entity must take these factors into account.
  • Whereas we may have many ‘Smart Building’ use cases now, to help us manage our day-to-day activities at home for example, we are farther away from the management of ‘Smart Cities‘ as this would take coordinated infrastructure development and collaboration. This might be easier in China, where there might be mandates and requirements, but in Western countries where many parties get a vote, it’s a much greater challenge. 

Below is a compilation of best practices to ensure sustainable implementation and execution of Smart Building initiatives.

  • Minimize latency issues so that selected users can efficiently receive not just the data, but the recommended actions based on the data received.
  • Focus on the most relevant use case, and solve that specific problem, which can be expanded to solve other problems.
  • Focus on the short term wins around Smart Buildings, then expand to other use cases which leverage the same technology, but outside the home, or at work. 
  • Focus on the long term play around Smart Cities, but build standards and collaboration to ensure the coordinated implementation of solutions.
  • Create model solutions including model cities and intersections to test solutions and technologies and their relevance and effectively for individual types of users. 
  • Develop integrated solutions to help employees better manage their logistics and planning around meetings and development or operations.
  • Create Smart Home/Smart City solutions which focus on the goals of safety, efficiency and quality of life, while conserving energy and optimizing performance.
  • Take advantage of smart building solutions which speak to current pandemic-related challenges including robotic automation for warehouses, disinfection management which keeps humans safe, commercial deep cleaning.

We ended the roundtable with some key open-ended questions:

  • What are the opportunities around the challenges posed by 2020 – the year of the pandemic and the myriad of resulting implications?
  • What are the long-game solutions around Smart Buildings/Smart Cities which take minimal investment dollars, so that we can prove value/warrant investment?

Please join me in thanking our hosts at Amazon, and our participating executives. 

Data is the New Black

November 16, 2020

FountainBlue’s November 13 VIP roundtable was on the topic of ‘Data is the New Black’. Please join me in thanking our participating executives and our hosts at Micron for framing the discussion.

November 13, 2020 Roundtable: Data is the New Black

It’s a given that each executive from each industry is impacted by data, so all were challenged to provide a provocative perspective on how data is and will be impacting our businesses, our industries, our daily lives. Below is a summary of my discussion.

The executives agreed that the data volume, velocity and variety is constantly growing. The challenge and the opportunity is to collaboratively delivering VALUE, while focusing on the needs of our customers’ needs.

Data is plentiful and growing, but finding the relevant and true data quickly will make the difference. Indeed, solutions which lead to valid conclusions, information, and solutions with limited data will become increasingly important. This is, in fact how the human brain functions… The trick is finding the most relevant kernels of true data.

One idea was to generate ‘fast data’ using AI and ML algorithms to make quick decisions based on specific criteria – like whether someone with little credit history is at high risk for defaulting on a loan.  
Others brought up the importance of examining edge cases – double-clicking not on what’s regular and normal, but finding patterns and learnings from the exceptional and different scenarios. From these anomalies, you may at times make a broader statement or conclusion – or just identify the anomaly as a one-off, a fluke. 
What’s important is to focus on the validity, the relevance, and the immediacy of the data, for if you’re not working with this type of data, you’ll have Garbage In, which would lead to Garbage Out (commonly known as GI-GO). The executives were in violent agreement that collaborating with others to validate data sources would lead to better decisions, better applications, better solutions. 
Several executives mentioned the need to focus on HOW data can solve many problems, and the importance of leveraging data to solve the most relevant problems, and the need to customize solutions, for there is no one-size-fits-all scenario.
Additional best practices include the aggregation of data from across departments, organizations, product lines and organizations will bring larger, broader perspectives which are relevant for all involved, and the need for ongoing collaboration to ensure elegant and ongoing data integrity, especially when milliseconds of time make a huge difference. An example is validating the signature between a nurse and a patient so that prescriptions are more quickly distributed, when timing is critical.
Everyone agrees that the data generated and gathered can help organizations run more efficiently, can help customers better understand what’s working, can help predict and capitalize on new strategies, can help deliver more relevant and richer customer experiences. 
With the rising dependence on the generation, storage and management of data, and especially now as the data is integrated into everyone’s day-to-day lives, we’re finding huge volumes of data generated on the edge. Responding quickly to the data on the edge will be a challenge, and filtering out the most relevant data will make the solution more effective and more efficient.
We ended with a call for collaboration, for standardization, for policy upgrades around data generation, privacy and security. The semiconductor solutions which gave Silicon Valley its name continues to develop the chips that power servers, machines, tools and devices. Innovations in the semiconductor industry in turn can support the data collection, storage, distribution, etc., tasks normally attributed to software solutions. 
Our executives concluded that Data can’t be the new oil, for oil is organic and more predictable. Data is defined, created, standardized, used by humans, and humans have decided that data will be everywhere. So humans must decide how to use it well, to solve specific problems. The need is urgent, the need is immediate, the opportunities are vast.

Automation Use Cases

October 9, 2020
FountainBlue’s October 9, 2020 VIP Roundtable: Automation Use Cases

FountainBlue’s October 9 VIP roundtable was on the topic of ‘Automation Use Cases’, conducted online with introductory remarks provided by our host company at Automation Anywhere. Below are notes from the conversation.

We were fortunate to have a diverse range of executives in attendance who shared a wide range of perspectives across organizations, across industries, across roles, across teams. 

It was exhilarating and exciting to hear of all the automation use cases envisioned, designed and implemented across industries by some smart, collaborative innovators and leaders. The future is bright for continued advancements in automation, providing more efficient, more effective support and information. Fundamental to the success of automation use cases is an understanding of:

  • the needs of the customer
  • the origination of, type of, format of and volume of the data produced
  • the processes underlying the solutions
  • the desired efficiency and effectiveness goal of the automation
  • the role of collaboration in the automation
  • AI to rapid process the volumes of available data and understand trends

One of the challenges for producing effective automation use cases is the latency involved in getting the right information to the right places/location/software/person. As we move from 4G to 5G, the latency get better addressed (going from 50 to 1 millisecond). Strategies for minimizing that latency were proposed.

Below is a list of potential innovations around automation.

  • Documenting transfer of property and information from one party to another
  • Humans training robots how to do what they do on the manufacturing floor for example
  • Further integration of 360 and other sophisticated cameras to better understand status before and after an event
  • Bridge between the AI which understands the data of the now/past to the Machine Learn – predicting a trend/action/pattern/event based on past data
  • Move between just the collection of data (what temperature is it) to the second degree of sensors which summarizes what a collection of data could mean and alerts the user (temperature plus respiration plus oxygen might mean infection)

Below are some best practices for producing automation use cases.

  • Test each software and hardware element independently and collectively.
  • Automate things that need to be frequently measured, processed in detail, etc.,
  • Provide actionable dashboards for the user.
  • Curate and collect data quickly and efficiently, filtering out what’s irrelevant.
  • Protect the privacy of users, but gather the aggregated data to make decisions, inform users, etc.,
  • Frequently track the time-to-value for your own company, and for your clients.
  • Figure out what’s true data, and only include the data that’s true within the offering you’re providing.

The discussion turned to the role of humans in automation use cases (process automation vs attended automation). We concluded that humans will never be obsolete and we listed specific circumstances where humans are needed.

  • Humans will have to be the decision-maker/fall-guy (or girl). This can not be delegated to a robot or hardware or software.
  • Humans decide what data is important and how important for what scenarios. In other words, the automation use case is generally designed by humans.
  • Humans need to evaluate the automation use case and make improvements. 
  • Humans define how to make the customer experience valuable for each type of customer – something which may not be inherently logical.
  • Humans have the creativity to solve a problem whose solution is not logical.
  • Humans know best how to bring the joy and passion to other humans.
  • Humans will have empathy for other humans, something difficult to program in. 

We conclude by looking at hybrid models, where humans and robots with hardware and software elements are fully integrated. What would it take to make this happen? 

All industries, all companies, all people will be progressively impacted in ways big and small by automation. Embrace this reality and do your own part in leading and innovating so automation is well integrated into your work and life. And while you’re doing it, make sure you’re focusing on the ‘human’ problems, not just the business opportunities which are profitable for some.

Please join me in thanking our hosts at Automation Anywhere, and our participating executives.