EA 874 Blog Topic 7 Evaluating emerging technologies, influential technologies and the future 

Dominic Patruno 

 

 

Ways to encourage company innovation 

Companies should rely on the following list of ways to try and bring innovation to their company.  This is not an exhaustive list, but some of these have been successful at some companies. 

Create an innovation incubator (Seiman, M).  This is where companies can stand up department or division that is dedicated to innovation and ideation.  The success comes by allowing anyone to participate in the innovation and ideation programs, but by having a department dedication the formal process of tracking and measuring the innovations programs can be handled by the department and or division, leaving the employees to focus on the innovation part entirely.  

Build a culture of experimentation (McGough, H).  Teams in all groups and departments should be testing ideas to understand what works and what doesn’t.  the idea of fail faster fits right in here.  Companies should accept a certain amount of risk in their experiments, because without knowing what doesn’t work, it is difficult to know what will work.  This is typically a difficult concept for most companies to actively participate and fund things that might not work, but with every iteration, they learn more and can apply that knowledge moving forward in much quicker and pragmatic way. 

Focus on customers (Trajman, O).  valuable innovation is when it can make a direct correlation, back to the customer.  By putting yourself in the shoes of the customer it is easier to identify with them, therefore innovating on the side of the customer.  This is very important, as customers are the life line for business.  No customers, no business.  Therefore, innovation that is customer focus will have a greater return.   

 

 

Emerging Technologies 

The Law Dictionary considers emerging technology to be technologies that substantially alter business and social environments.  These environments include technologies wireless communications, bio technologies, advanced robotics and artificial intelligence.  Emerging technologies be suspect and in turn not really embraced by most.  Eventually these technologies take shape the majority will find benefit in them.  The following are emerging technologies that are currently being developed and introduced into the public for 2017.   

Self-driving trucks are making their way into the emerging technologies list as are autonomous vehicles.  For similar reasons.  Self-driving trucks could save companies millions in labor hours and safety.  People, will become fatigued, but computers will not.  This could let companies round their truck delivery services around the clock with less labor hours and not human fatigue.  Additionally, there could be less accidents and insurance costs.  This, technology is still in its early stages, and must also get approval from the government to operate on public streets. 

Powered exoskeletons; currently people who are handicapped in walking only have the alternative to use wheelchairs.  However, technology in exoskeletons is becoming more affordable and practical.  Paraplegics can now walk up right, which can lead to a healthier and better quality of life.  Another use is for emergency responders, who may use the exoskeleton to augment their strength and lift large amounts of rubble to help search for survivors.  Additionally, the US military could use the exoskeleton to help soldiers walk further without fatigue and carry more supplies. 

High-speed transportation is moving from theory to reality.  With the proof of concept trials of the Hyperloop and computer mock ups of the Evacuated Tube Transport the reality of travel across the globe in minutes vs. hours is coming closer to reality.  Globalization has made international travel a necessity and time is money.  Taking 12-16 hours to fly to Asia, or 4 hours from New York to LA, this is just too long.  Though the first generation of these methods of transportation will be fairly expensive; If those times can be shortened people would be willing to pay.   

 

 

 

 

Innovation Programs 

The company I work for has just introduced an innovation program.  According to the Gartner (Fenn, J, Harris, K.) document I would consider our program to be a level 2 maturity.  We have a program in place and have staff members working on the innovation team, but lack defined processes and at times it seems more of a technology trial and error rather than a formal program.  Typically, technologies will be evaluated and researched, but no formal analysis will be done to see if there are any benefits.  This team is also responsible for what we call our incubation program.   The purpose of this incubation program is to define how technology should be introduced into the organization.  We are yet to define a consistent and repeatable process to do this.  I think that is where the focus needs to be, according to most innovation maturity models, it is important to evolve to a defined process and make sure it is repeatable.  According to Gartner that is the level 3 maturity.  Where I think we need to improve is in the process of how we evaluate the technologies as they align to our strategic objectives, what innovation process we use and how the technologies are then introduced (or not) into the environment.  We are yet to have an end-to-end successful innovation deliverable, that maps to any strategic objective.  

 

 

References 

Dennis, R. September 2014. Top 10 Emerging Technologies that are changing the world.  Retrieved from http://www.makeuseof.com/tag/top-10-emerging-technologies-changing-world/  

Fenn, J, Harris, K.  April 2011.  A Maturity Model for Innovation Management.  Retrieved from https://www.gartner.com/document/1621015?ref=TypeAheadSearch&qid=f7861f7b9bf3860171c6390  

McGough, H.  Lean Start Up Co.  Retrieved from https://leanstartup.co/about/ 

Seiman, M. Digital Remedy.  Retrieved from http://www.digitalremedy.com/about-us/  

Trajman, O. November 2017. 18 Ways to Actively Encourage Company Innovation.  Retrieved from https://smallbiztrends.com/2015/09/encourage-company-innovation.html 

Retrieved from https://thelawdictionary.org/emerging-technologies/  

Retrieved from https://www.technologyreview.com/lists/technologies/2017/  

Dennis, R. September 2014. Top 10 Emerging Technologies that are changing the world.  Retrieved from http://www.makeuseof.com/tag/top-10-emerging-technologies-changing-world/  

 

Business Architecture

 

The definition of business architecture, is to provide a common and consistent view and definition of the organization and to align strategy with tactical execution. Business architects are known as the subject matter experts that perform this type of work.

Though there are quite a few success stories with the practice of business architecture, the message is not resonating with senior leaders. Business leaders are just not understanding the value as they seem to think because the business is “marginally” successful and there is no need to change. However, other companies that have implemented a business architecture group are seeing greater returns in productivity revenue increase in double digits, as well as a more efficient work force.

Business architecture has some great benefits, which includes; establishing transparency across business units, product lines, cross functional teams, and the overall business vision. Allows for the creation of road maps so clear blue prints are established and can be understood and followed across the enterprise.

Miscommunication amongst departments and division is one of the key inhibitors to companies being successful. Business architecture helps companies create that common vocabulary and lexicon when discussing things like customers, profit, product, and vendors. Poor communications can create situations that lead to duplicative work or poorly implemented process and or systems, and could also lead to missed opportunities, and loss of revenue. The example below is a real-world scenario.

 

A company’s IT infrastructure group was trying to implement an enterprise wide monitoring solution for the infrastructure systems. The infrastructure group made assumptions in requirements that were needed at the divisions and the site level.   This caused the solution to continue to be in re-work and re-configuration mode because the implementation team continued to struggle to re-architect whilst rebuilding. A local site team, ended up developing their own monitoring solution through custom development and freeware tools. The amount of time and money spent so far, and we still do not have a consistent enterprise monitoring solution. Architecture in general could have enabled this to be a successful deployment or at the very least, would have showed that this would not have worked to begin with, without the investment in all the time and money.

 

Digital Business

 

Digital has become the latest buzz word with regards to the next generation of business.   The question is what does that really mean, digital business?   Some describe digital business as business that has an internet presence, or a business that has a web site, maybe takes payments over the internet. I think it is much more than that. Digital business is all things digital to enable the business. For example; automated business processes, data driven decision making, continuous improvement and having a direct and immediate pulse on your customer’s needs and wants.

Three fundamental changes when transforming your company to digital are, recruit talent that is enthusiastic about the vision and technically proficient, prioritize speed of delivery over perfection and introduce a mile-stone based method of project delivery. Very iterative and keeping continuous improvement in mind.

Recruiting talent, has changed in the sense of the who and how. Talent in the digital world consists of expertise in the following areas, data science, IoT developers, user experience design experts, and product owners. These are quite different than the traditional, software developers, server and network engineers and ERP engineers. The way to recruit this talent has changed as well. No longer can we rely on traditional job postings in mainstream job sites or periodicals. Companies must use multiple channels and market and sell their brand like selling a customer they must convince an employee prospect as to why work at their company.

In addition to retaining top talent, digital businesses must adopt a concept of fast iteration. Either with their products or services or both. Working a product to perfection will almost certainly take too long to deliver and another company will almost certainly beat you to the punch. Companies need to think of the minimal viable product and be sure that what they are delivering is something the customer either wants or solves a problem for them. Otherwise, there really is no need to have the product or service.

Follow the data; digital businesses need to understand the value of data and begin to use the data to make decisions. If something is not selling or customer response is less than desirable companies must understand this quickly and adjust their products or services. The only way to understand this at a fast paced is to create a data analytics solution that allows for this type of information to be gathered, analyzed and acted upon.

 

Business Architecture Failures

Why has it been so difficult to implement business architecture in the enterprise? One reason could be that the role of enterprise architecture is not fully understood and can sometimes be confused with other roles such as business analysts, systems analysts and requirement engineers. Given this ambiguity it can be confusing for leaders to understand the value and at which level in the organization. The industry has also created confusion in that Business Architecture has not been promoted as something that falls under the umbrella of Enterprise Architecture, thus giving it some clarity and relationship within the organization.

What should companies do to implement a successful Business Architecture program? At a very high level start small, enlist executive support and have a clear and direct line of sight into the value of the program and its deliverables.

If there is a new transformational initiative underway, this might be a good opportunity to enlist a business architecture approach. Ensure there is executive support and understand the roles and deliverables by all parties. It is important to capture lessons learned, as there will probably be many and continue to improve the process and the documents. This is an iterative process and should have a continuous improvement loop as part of this program.

References

Retrieved from http://www.bainstitute.org/resources/articles/business-executive%E2%80%99s-view-business-architecture

Retrieved from https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/upgrading-your-business-to-a-digital-operating-system

Retrieved from https://blogs.msdn.microsoft.com/nickmalik/2012/04/06/the-difference-between-business-architect-and-business-analyst/

 

Vulnerabilities

 

We all my have heard about the Equifax security breach. The core of the issue was an attacker was able to exploit a known vulerablilty in one of their web servers. This exploit allowed the hacker to gain access to the internal network and ultimately steal personal information such as social security number, driver license number, name and address among other personal information for roughly 143 million customers.

The vulnerability was discovered and a patch was released in March of 2017. This means that the Equifax patching team had over two months to patch the vulnerability which would have thwarted hackers attempts to comprimise the system. Hoevere, Equifax did not patch their systems and the data was stolen sometime in mid May of 2017. Things got worse from there. The company did not report the breach for another six weeks and there were also reports of seniro executives selling Equifax stocks prior to the public being notified of the breach.

In investigation is still ongoing, but it is clear, all security architecture, processes and procedures completely broke down at this company. As we move faster with the implementatiions of technology and with machine learning and AI becoming more pervasive in our personal and professional lives. It is imperative that not only individuals, but companies step back and take a hard look at their security architectures and risk management. This was a completely avoidable event and should never have happened.

 

 

 

Data Security

With the increase in devices that create data and the systems that use data, there has been a paradigm shift in how to security data. Typically, in the past, data has been secured in siloed application or file share. Users with access would then consume the data form those locations. IN this model there were many security measures in place, but limited to the systems and file stores. Now, we must look at how to secure the data itself, regardless of its location.

Data classification is almost as elusive as big foot, companies like the idea but rarely implement such a process.   As we explode with data, we need to understand the type of data we are generating and what type of risk it opens. For example, data that may be generated from systems that show general health or telemetry data should not be protected in the same way as some financial or intellectual property data. Therefore, there should be a multi-layer approach and security should be applied to the data regardless of its location.

Security controls need to adapt to the new way data is used and how it is transferred. Companies should start taking a more risk based approach to data security. Additionally, they should start leveraging technologies such as application firewalls, certificate and multi-factor based authentication. Ensure backups are stable and solid and test restores. Encrypting all data, data should never be stored or transferred un-encrypted. Lastly companies should constantly test their controls. You never know where your weaknesses are until you test and you never know what can be possible until you test against that threat. This helps fortify areas that may otherwise be weak.

Encryption

Encryption is the process of changing the presentation of information in a way that is unreadable to others unless they have a key which deciphers the data back to its readable format. With the explosion in the amount of data created; encryption has become more popular because a lot of this new data could be very damaging if it were to be compromised.   Companies, governments and individuals have been using encryption to secure data for years. The challenge has always been keeping up with the encryption algorithms. Because faster computers and more intelligent algorithms keep cracking the encryption. For example; DES was one of the first encryption standards used, and has since been replaced by triple DES and other encryption standards due to its vulnerability to be cracked by high performing computers.

With the recent data breaches and more ransomware attacks, companies will begin to escalate their encryption competencies and start to use this as a strategic position to protect their customers data and their intellectual property.

 

References

Chicago Tribune. (September, 2017). The Equifax Breach: What lesson will other companies learn?. Retrieved from https://search-proquest-com.ezaccess.libraries.psu.edu/docview/1938147054?pq-origsite=summon&https://search.proquest.com.ezaccess.libraries.psu.edu/usmajordailies?accountid=13158

Wikipedia. (September, 2017). Retrieved from https://en.wikipedia.org/wiki/Equifax

Gerber, S. August 23. 13 Ways companies should improve their data security in the age of IoT. Retrieved from https://thenextweb.com/entrepreneur/2016/08/23/13-ways-companies-improve-data-security-age-iot/

 

Dominic Patruno

IoT

 Internet of Things also known as IoT is a network of devices embedded with software, sensors and actuators all connected together collecting and possibly transferring data (Wikipedia, 2017).  The purpose of IoT devices is to connect the physical world with the computer based systems to track, monitor and these devices with increased efficiency, accuracy and limited human intervention.

IoT has been in use for quite some time, the airline industry has been using sensors to monitor engine performance and maintenance for years.  However with the ever increasing growth of IoT devices and the use not only in commercial but now consumer spaces, it is important that security be part of the architecture and support moving forward.

More and more devices are being connected such as phones, fitness trackers, automobiles and watches, those devices and the data they collect become a target for hackers.  Manufacturers and consumers must be vigilant in the security of their devices and ensure they are kept up to date in software updates.

As manufacturers and consumers enter the IoT space, they need to consider the following best security practices.  Data collection, understand the terms on how the data is collected and used, additionally be sure how the data is transferred and to whom.  Keep up on the how devies are secured and how the companies are looking to keep their devices secured.  Security threats are constantly evolving and so should the products to address them.  Stay informed of legislation that will govern privacy standards for consumers, be sure the products you purchase and or manufacture are adhering to these practces and governance.

 

Edge Computing

Edge computing is the processing of data at the edge of the network closet to where the data is being captured (Wikipedia, 2017).  This edge computing uses cloud computing technologies to process and analyze data and makes decisions before sending the data to a central repository, typically in a centralized data center or hybrid cloud.

The difference between edge computing and just having servers on premise is the purpose and the technology.  In the case of having on premise servers for computing was to delivery applications.  In this case the main goal of edge computing is to deliver data processing and analytics, while reducing network bandwidth requirements and data latency.

As more and more IoT devices become embedded in our organizations, and begin collecting more data.  It will be imperative that we start to create these edge computing environments as data collection and processing points to handle the sheer volume of data.  Additionally, these edge computing environments can act as continuous improvements hubs that analyze data and act based on the analysis.

I believe this is still a new and evolving technology and will continue to mature and adapt to the needs of the market.  Vendors such as Cisco, Microsoft and Google are watching very closely and placing bets where they feel they can make a difference.

 

Wearables

Wearable technology is technology that can be worn on the body and is typically connected to the internet either through a smart phone or its own network connection.  Currently wearables are mostly novelty items, in that they are typically used to track health, stress and sleep monitoring.  There has been some clothing made that will light up and create designs with lighting, also some glasses that allow for embedded documents to display and the ability to take picture and stream live data.

As the technology enhances and the laws become more supportive of wearables, I think we can se greater value and effectiveness in their use.  For example, in sports, if a shirt could monitor and track the health and stamina of a player, they could then use that information to know when to rest or keep the player in the game.  Giving them a competitive advantage to their opponents.  Additionally, the same technologies can be used for patients that are being monitored for stress tests.  Instead of sending the patient home with electrode connections and a data gather box, they just need to wear a special shirt.

Glasses can have many different applications as well.  For example, in manufacturing, when a technical is building a car or even kitting a multi-part product, there could be instructions that are visible through the glasses providing real time instructions and offering better quality and speed to the assembly process.

In summary as IoT grows, I think the wearables market will grow as well.  Similar to IoT, security will need to be top of mind for manufacturers and consumers.

 

 

References

Retrieved October 6, 2017 from https://en.wikipedia.org/wiki/Internet_of_things

Joyce, S. (August 2017).  The Next Stage in the Evolution of the Internet of Things – Security. Retrieved October 6, 2017 from http://usblogs.pwc.com/emerging-technology/evolution-of-iot-is-security/

Retrieved October 7, 2017 from https://en.wikipedia.org/wiki/Edge_computing

Retrieved October 8, 2017 from https://en.wikipedia.org/wiki/Wearable_technology

 

 

EA 874 Blog Topic 3 Data / Information Architecture Layer

Dominic Patruno

Data Breaches

Its difficult to discuss data and information without addressing the ever increasing data breaches. Some being very significant lie the recent Experian data breach. According to reports (WindowsIT) hackers were able to obtain ove 143 million records. This include names, social security numbers, driver license numbers and credit card numbers among other personally identifiable information.

Though the Experian data breach is an extreme case of data loss. Most companies, have some level of exposure when it comes to sensitive data. Most companies, are not even sure where all of the data lives and how it is transported around the company. Companies due implement control measures, such as data loss prevention and information rights management tools, but without proper classification of the data. How does one know when and were to apply the proper policies and controls.

The volume and velocity of data is only growing, and companies will need to have a proper data/information architecture in place to account for this and should start sooner rather than later. I can see where data architecture could be a differentiating factor. If these types of braches continue, government might get involved and require proper controls similarly to what happened with the Sarbanes Oxley act.

 

Data Architecture

Data architecture has become a very important practice to companies and is important to stay competitive if not relevant as companies become more digitally enabled. 70% of employees have access to data they shouldn’t while 80% of analysts’ time is spent discovering and preparing data (Dallemule & Davenport, 2017).

One the biggest hurdles to implementing data architecture, is where to start and trying to boil the ocean. If companies have not had any real data architecture in their enterprises, then they would want to start small with achievable milestones that deliver the best value for the effort.

Some experts agree with starting with “Single Source Of Truth” (SSOT) data. Usually this is customer, financial and supplier data. Most everyone can agree what system houses this type of data and how it is represented. Another element that will make data architecture successful is data governance.   This is very important, because there should be rules on how data is created, used, labeled and destroyed. This can also help with mitigating data leakage risks.

 

 

Another approach is to take either a defensive or offensive position with regards to data architecture and strategy. This could help set the scope and provide buy in and support from senior leaders and executives. The following table illustrates the difference in each position.

 

The Elements of Data Strategy

	DEFENSE	OFFENSE
KEY OBJECTIVES	Ensure data security, privacy, integrity, quality, regulatory compliance, and governance	Improve competitive position and profitability
CORE ACTIVITIES	Optimize data extraction, standardization, storage, and access	Optimize data analytics, modeling, visualization, transformation, and enrichment
DATA-MANAGEMENT ORIENTATION	Control	Flexibility
ENABLING ARCHITECTURE	SSOT (Single source of truth)	MVOTs (Multiple versions of the truth)

 

Data architecture is extremely important and companies that are not taking this data architecture seriously are in danger of being either bought or go out of business. Keep in mind data architecture is something that is iterative and needs to be designed with continuous improvement and agility going forward to be successful.

 

Data Is More Valuable Than Oil

If we look at some of the biggest tech companies today, Google, Amazon, Apple and Facebook, we can see a patter in how they use data to advance their business. Google with their search engine data, Amazon with their purchasing data, Apple and Facebook with their advertising data and it continues to grow. This leads to companies acquiring more data to make better decisions, which leads to capturing more data to make better decisions.   Along with tools such as AI and Machine Learning this only enhances their knowledge on how to better sell and market to the customers.

 

 

 

 

 

 

 

 

 

References

Retrieved September 20, 2017 from https://www.washingtonpost.com/business/technology/what-you-need-to-know-about-the-equifax-data-breach/2017/09/09/46d20dc4-957d-11e7-8482-8dc9a7af29f9_story.html?utm_term=.bcb7489a9cec

Dallemule, L. & Davenport, T. (2017, June). What’s Your Data Strategy. Retrieved from https://hbr.org/2017/05/whats-your-data-strategy

Hunt, T. (2017, September). The Trust Problem with Equifax. Retrieved from http://ezaccess.libraries.psu.edu/login?url=https://search-proquest-com.ezaccess.libraries.psu.edu/docview/1936769277?accountid=13158

 

EA 874 Blog Topic 1 Digital Disruption and Stack Overview; Cloud Technologies Influence 

Dominic Patruno 

Digital Disruption 

What is digital disruption?  As described by Riemer and Johnson, digital disruption is the changes to social interaction, business and value creating using technology.  One of the best known digital disruption companies is Amazon.  With their store front, Amazon Web Services, Amazon movie and content services, same day delivery and now personal assistant technology Alexa.   They also just recently announced the desire to acquire Whole Foods to disrupt the supermarket business.  They are constantly challenging and changing the way we do business and disrupting markets and businesses in their wake.   

When I was a boy, we used to take pictures with a camera that we would have to purchase film for.  Once all the film was used we would take it into a store to have the film developed, this would take a week or two depending on the vendor.  Then 24 hour which became 1-hour photos became popular and those film developing businesses either evolved or went out of business.  Now you can use your smart phone and either print your digital picture at home or at a drug store such as Walgreens or CVS and have the photos almost instantly. 

These types of digital disruptions are still here today but are occurring far faster and with more advanced technologies.  Let’s take Alexa, the personal assistant.  With this tool, you can turn your lights on and off, order a pizza, play a movie and call or text your family and friends, all with voice commands.  Think of this type of technology in the work place.  Giving voice commands to personal assistance that prepare your expense reports, collect, generate and print reports of customer spend or new leads.  The applications are endless.  Companies are going to need to create a foundation for executing to keep up with these digital disruptions or risk being put out of business. 

 

Cloud Technologies 

Cloud technologies is a necessary foundation for the digital age.  Companies that want to be nimble, cost effective, and data driven will need to embrace some level of cloud technologies.  Whether they are leveraging Software as a Service, Platform as a Service or Infrastructure as a Service, these core capabilities will be key to enabling the digital business platform and creating a competitive advantage.  Software as a Service (SaaS) is key to providing software to enable the business for very routing types of business applications and services.  This is the technology where there is very little administration, no hardware or software to purchase and provides a consumable service to the business.   

Platform as a Service (PaaS) enables companies, by allowing them to develop and deploy applications rapidly, along with deploying applications closet to the end user.  This is less costly then renting data centers, buying servers and storage and deploying applications typically out of one region.  With PaaS you eliminate all of that overhead and move to a quicker pay as you go model. 

Infrastructure as a Service (IaaS) also provides a cost and agility benefit to organizations as this also relieves the burden of purchasing servers and storage, as well as network and software to support the infrastructure.  It provides companies the flexibility to provide server and compute workloads with an elastic capability.  Sometimes companies may need to ingest a tremendous amount of data and do some level of data analysis.  They can spin up terabytes of storage to stage the data, and spin up multiples compute serves to do the processing of the algorithms, once the analysis is done.  They can turn off all the resources and only paid for what they used.  If this was done in a local or leased data center, companies would still need to purchase the storage and computer hardware.  Once the analysis was done, what would they do with all that hardware that they did not need. 

In summary Cloud Technologies is becoming the new utility services for the digital age.  We should embrace cloud technologies, but ensure we are clear as to how we are using these services and mindful of the impact to our operations and security. 

 

 

EA Stack 

The Enterprise Architecture stack is actually quite intuitive in that all flows from the business, to business operations to systems that support the operations to the technologies that support the systems.  This allows for end to end alignment.  Once mapped, this can help with changes to the architecture at any of the levels.  If a business process changes, one can understand the entire ripple effect by looking through the Enterprise Architecture Stack.  For example, there is a change in the PO process; The Enterprise Architects can review what in the business operational process is being changed.  Then can look at all of the impacts in the information and data architectures or any application architectures that maybe impacted.  Additionally, but less likely, there may be a change required in the technology stack.  These stacks can all be updated based on the new process as necessary, all relevant parties can be trained and informed.  Without this level of architecture, what usually happens is systems, processes and procedures break down. 

References: 

Riemer, K., Johnson, R. (March 7, 2013). What is Digital Disruption. Retrieved from https://byresearch.wordpress.com/2013/03/07/digital-disruption/ 

Retrieved from https://www.amazon.com/p/feature/rzekmvyjojcp6uc  

Gray, M. (October 21, 2010). Cloud Computing: Demystifying IaaS, PaaS and SaaS.  Retrieved from  http://www.zdnet.com/article/cloud-computing-demystifying-iaas-paas-and-saas/  

 

 

Chatbots are one of the newest disruptive technologies in today’s business application landscape today.  Categorized as “apps” for voice and text messaging platforms, chatbots allow users to interact with digital business services and data using their spoken language.  Driven by the ever-expanding application marketplace, the Internet of Things (IoT), advancing cognitive Artificial Intelligence (AI), and conversational interfaces, chatbots are being propelled into our everyday lives.

From an EA perspective, our concern the increased usage of chatbots on personal devices will give way to a Bring Your Own Virtual Assistant (BYOVA) into the corporate environment. The implications on information security cannot be underestimated because each request delivered to a chatbot is a proxy for a user request. 

Most Enterprise Software solutions are incorporating this function into their products, the concern will be that in some cases the chatbots from different system might conflict, causing confusion and potential errors within the business processes. 

In summary, chatbots are gaining in popularity and this is a very disruptive technology.  Enterprises should be vigilant and establish governance and policy quickly to address this emerging technology.

Humans vs. machines, both have systems and both perform functions and tasks, but there are many differences that separate humans from machines.  First machines are created by humans and therefore their level of knowledge have been programmed into their computers by humans.  Machines do not have feelings where humans do.  Humans can feel pain and emotions, where a machine has no feeling of pain or emotions.  Humans are made up of organic material and are living systems, where machines are made up on non-organic material and systems that are programmed. 

Many have speculated that machines could one day take over the world.  I guess it is possible given the advancement in artificial intelligence and machine learning.  Machines could begin to learn on their own and then could possibly surpass the intelligence of humans.   This would probably be in the far future if ever.  Until then I think leveraging machines to help humans accomplish tasks and functions quicker is a good thing.  One thing that humans and machines do have in common is that we are ultimately made up of stardust and therefore come from matter that makes up the universe.

I recently read an article about digital services in the automotive industry and how the industry is changing from a mechanical to a more digital user experience.  Before, automakers would appeal to the customer by creating backup cameras, hot/cold seating, larger leg room, elegant looking trim and dashboard accessories.  Digital has changed all that.  Today automakers are focusing on a fully immersed experience that includes, video, artificial intelligence, pattern and profile recognition and crowd sourcing.  By leveraging information about how the customer travels, where they travel to and how long they are in their cars, automakers can create a customized and relevant experience.

For example, if the automakers digital platform know that you travel a specific way to work each day, it can use all its data feeds from traffic news, weather reports, emergency management updates and, artificial intelligence to suggest new more efficient routes to work.  This information can be sent to the customer via a smart phone or in some cases a smart mirror in a connected home. 

Ultimately the end goal is still the same, give the customer what they want.  The how has definitely changed, and is the secret sauce that will separate the automakers that continue to evolve versus the automakers that just fizzle out.

 

References:

Tian, J & Chin, A (2016, December) Digital Services in the Automotive Industry.  Computing Edge Hot Topics, 28-31.