ACMPaperFinalDraft.docx (5)

1
Cloud Enabled Adaptive Case
Management for the Age of the
Customer
Linus Chow and Casey Conner, Salesforce;
Sherry Comes, Genpact; Jin-Lin Mei and Tom
Bullotta, Acumen Solutions
EXECUTIVE SUMMARY
We are living in a customer-driven era where technology is evolving around the way
consumers think, communicate, work, and purchase. In today’s digital world, customers
expect all of their technology to be easy-to-use, modern, and connected. Customers expect
consistent and high-value in-person and digital experiences. They value a deep understanding
of who they are and the anticipation of their needs. Adaptive Case Management use cases are
driven to meet this higher expectation. Organizations are forced to transform their legacy
systems and processes to a knowledge-based architecture that can be dynamic, variable and
unstructured. Successful transformation is the difference between a thriving business or
extinction. Thankfully, the same forces changing the customer's expectations have also
produced new cloud capabilities that can provide a system of engagement layer to keep pace
with customer demands. Welcome to the Age of the Customer!
INTRODUCTION
Today’s customers are more powerful than ever, with the ability to shift markets and define a
company’s success in a matter of seconds. They’re not looking for products, features, or
gimmicks; they’re looking for a complete and effortless customer experience. They don’t just
want to solve problems; they want to build a faster, smarter future — and they’re disrupting
entire industries in the process.
Seismic shifts in people, processes, information, and technology are creating enormous
pressures on how businesses keep their organizations competitive and their customers loyal.
This is nothing short of a revolution — the fourth industrial revolution, a blurring of the
physical and digital worlds — with customers at its center. This journey to the Age of the
Customer is a confluence of changes in technology and how humans have adapted and
accelerated those changes.

CLOUD ENABLED ADAPTIVE CASE MANAGEMENT FOR THE AGE OF THE
CUSTOMER
2
Figure 1: Journey to the Age of the Customer
The Journey to the Age of the Customer has been an intertwined evolution of technology
advances and how people have adapted to take advantage of it. This has also driven an
exponential growth in information and connectivity; and more dynamic and adaptable
processes and architectures.
The relationship with the customer is now more important than ever, and must be more
holistic, deep, and real-time relevant. CEOs and Business Executives see a knowledge-based
architecture as a strategic platform not only for retaining existing customers but also for new
business innovation and ecommerce. This presents challenges for the CIO/CTO in delivering
Digital, Social, and 360-degree connected experiences on a Modern Architecture, while
dealing with legacy, security, compliance, and governance challenges. Cloud Capabilities and
Modern Architectures enable Adaptive Case Management to transformorganizations to meet
the rapidly changing customer expectations.
“Modern Architecture” is a fresh look at how enterprises shift toward combining both new
and existing technologies, specifically cloud technologies. Such architectures are rooted in a
number of basic realities:
● Smart “hybrid” application design: the data locked in on-premises and legacy
systems and devices needs to be quickly “surfaced” to the cloud through lightweight
integration, API-first thinking, and in-memory analytics—in some cases cutting
delivery to hours instead of months.
● Agility as a way of life: rapid prototyping, effective product owners, and visible,
defensible backlogs must be supported by the next wave of practitioners.
● Future-proof by design: changing process automation requirements, Internet of
Things (IoT), and other data-intensive trends are forcing applications to evolve
rapidly. Metadata-driven platforms provide the right flexibility to allow architects to

CUSTOMER
3
pivot and act instead of react. Also, support for both model-driven and elastic
approaches are critical to success.
● Developer democratization: conventional development approaches are giving way to
“composability” – ranging from drag-and-drop component assembly to functional
components that can be “snapped into” the ecosystem. Tooling needs to continually
move up the “food chain” resulting in rich palettes for business users fromwhich to
compose and assemble (vs. craft by hand).
● Event-driven as a design point: the combination of the mobile revolution and the
coming IoT tsunami of big data shows a clear trend towards smart, connected “apps”
and the supporting ecosystembecoming much more event-driven and less procedural
and pull-focused. Truly, the very nature of how we meet such business demands will
cause disruption to the enterprise portfolio.
Figure 2: Fabrics Reference Model
Modern Architects can map current and planned portfolios to this model, identify integration
or process gaps, and then set priorities based on the combined Business and IT Roadmap.
What is liberating about Modern Architectures is the Enterprise can realize value
immediately, build initial momentum, and accelerate applications and services all while

CUSTOMER
4
effectively managing budgets.
Figure 3: Detailed fabrics Reference Model (sample)
As seen in the sample fabrics Reference Model above, providing fast-to-market cloud
capabilities allows for “Pace Layering” and Two Speed or Bi-Modal IT development. Rapid
customer-focused Adaptive Case Management use cases can take advantage of cloud enabled
fabrics, while slower Systems of Record can be modernized at their own pace.
The faster innovation provided by cloud capabilities across the fabric layers enables the next
step in the evolution of Application Development, Adaptive Case Management, and
structured Business Processes. In the Intelligence Layer, “wearables” are expanding to
encompass all types of devices, and “Data Discovery” is evolving into “Data Science” which
includes cutting edge predictive analytics and machine learning. This can be seen by large
investments by the leading cloud players. For example, Salesforce’s launch of IoT Cloud in
Sept 2015 (powered by Thunder) and investments in Artificial Intelligence (purchase of
MetaMind in April 2016).

CUSTOMER
5
Figure 4: Functional Capabilities of Cloud Architecture
With a Modern Architecture strategy, Adaptive Case Management can take advantage of key
cloud capabilities better suited for faster adoption and more dynamic change. An example of
the functional capabilities is shown above. We will explore cloud capabilities most relevant in
the Age of the Customer focused on three areas:
● Social, Collaboration and Communities: Customers expect omni-channel interaction
(mobile, web, in-person, social, etc.) with the same 360-degree of understanding.
● Internet of Things (IoT): People, Systems, and Things (machines, devices, sensors)
are more and more connected enabling new dynamic processes for both consumer
and industrial use cases.
● Artificial Intelligence (AI), Cognitive Learning and Neural Chat:
SOCIAL COLLABORATION AND COMMUNITIES (JIN-LIN MEI,ACUMEN SOLUTIONS)
Some experts believe that in the future we may no longer be able to tell the difference
between employees and customers. At first glance, that idea might seem a little far-fetched,
but consider the business model of a home-sharing service such as Airbnb. Homeowners use
the service to list their property on the company’s site and customers are looking for a short-
term rental. Travelers use the site to find lodging that may be cheaper or more convenient than
a traditional hotel. The company relies on both sides of that equation — so who’s a customer,
and who’s an employee?
In what is known as the “collaborative economy” or “sharing economy,” the lines between
customers and employees are blurred. In businesses such as home-sharing (Airbnb) and ride-
sharing (Lyft and Uber), a company’s value lies in its ability to connect peers to one another
— whether they’re homeowners and renters, or drivers and passengers. More and more

CUSTOMER
6
companies are learning the value of these peer-to-peer relationships — and building profitable
businesses based on peer-to-peer sharing and collaboration.
In a 2014 cover story dedicated to the rise of the sharing economy, Wired described it as an
economic and cultural breakthrough. It is also a resounding affirmation of the importance of
communities. Far from dividing people, the Internet and the rise of mobile and smart devices
has brought us much closer together than ever before. In fact, over 72% of customers prefer to
use a company’s website to find answers according to Forrester Research.
In this connected world, the demand for community and collaboration, both personally and
professionally, is undeniable. Even for businesses not founded on the principle of peer-to-peer
sharing, the collaborative economy presents important opportunities. The lines between a
company’s customers, employees, and partners may already be blurring and odds are, each of
these groups is looking for closer ties and more opportunities for sharing and collaboration.
According to research from the University of Michigan, customers in communities s pend 19
percent more than customers who are not engaged. So how can businesses take advantage of
this opportunity?
Figure 5: Value of Communities
Collaboration and Communities that connect agents to customers provide faster response
time, quicker connection to experts and faster resolution time for Adaptive Case Management
use cases.

CUSTOMER
7
Figure 6: Integrating Cases with Communities
Collaboration and Communities that connect agents to customers provide faster response
time, quicker connection to experts and faster resolution time for Adaptive Case Management
use cases.
Self-Service Customer Communities enable customers to help themselves and each other
deflect service calls and requests by sharing knowledge through articles and enabling
customers to ask and answer each other’s questions. Customer Communities extend the
service team’s ability to service customers by integrating cases into the community so that a
question in the community can be escalated as a case, which the agent can manage in a single
interface. These cases can be created automatically and routed based on keywords or topics.
This speeds the ability to resolve cases quickly. Customers can create and interact with cases
through multiple channels (website, mobile, voice, and IoT, etc).
In addition, the ability to actively listen to what customers are saying about the business,
regardless of whether it is positive or negative, is critical to support a proper and timely
response. In an age when social media is an outlet for anyone to share his or her opinion
without solicitation, companies have an opportunity to capitalize on the information shared
via social media. For example. positive reviews can be shared to help promote a corporate
brand, while negative reviews can be rectified quickly to show the commitment to making
customers happy. An example can be seen in Acumen Solutions’ Smart Information Filtering
Tool (SiFTTM) solution:
http://www.acumensolutions.com/resource/smart-information-filtering-tool-sift
An example of omni channel collaboration between customers and service agents can be seen
by Intuit’s success story. https://www.youtube.com/watch?v=CEKMRU1o-wE
Social, collaboration and communities bring together the stakeholders both inside and outside
an organization to better solve a customer's problem. This adaptive and personalized
responsiveness is expected in the Age of the Customer and provides a basis for additional
connected and “smart” services.

CUSTOMER
8
INTERNET OF THINGS (IOT) (TOM BULLOTTA,ACUMEN SOLUTIONS)
We are in the midst of a customer-centric revolution. It’s driven by new consumer
expectations and it’s changing everything. The third wave of applications, connected services,
is enabling smart connected products and devices to meet those expectations -- whether it’s
your car helping you schedule a service appointment when its oil is low, a vending machine
requesting replenishment for a low stock condition or a health monitoring device contacting a
medical technician when your vital signs are out of threshold.
Devices in the Internet of Things (IoT) are at the core of this transformation. They generate
massive amounts of data and companies have started to capture and store billions of data
events every day. But storing it isn’t enough. This revolution is about proactively engaging
systems and people to resolve issues or grab opportunities. Responses must be intelligent,
actionable, personal, and in real-time.
The Internet of Things represents a major and transformational wave of IT innovation. The
Harvard Business Review calls this the third wave of IT driven competition, with the first two
waves brought to you by mainframes and minicomputers, and the rise of the Internet.
Needless to say, harnessing and analyzing these data streams will represent the biggest
challenge IT and businesses will face over the next decade. The IoT wave of innovation is
forcing us to change the way we both create value and capture value.
Value creation, is essential for a viable business model. These are activities that differentiate
a company’s offering so that a customer is willing to pay more for it. Traditionally, feature
and price drive the viability of the offering. Eventually, the offering matures and becomes
obsolete. But with a connected IoT Cloud new capabilities can be added regularly for much
longer. Also, not only can more customer data be collected; there are more potential
connections that can provide even more customer insight and opportunity for direct customer
engagement. Manufacturers, for example, increasingly can connect directly to end customers
and move into servitization versus previously having a distributor as a middleman. Derived
value is not only in new revenue, but further boosted by cost savings through process
optimization and intelligent operations.
Value capture is also transformed due to cloud architecture. Different monetization strategies
occur not only from a customer value standpoint, but also from the information gathered
through a firm’s connected people, systems and things. Leveraging data from connected
products in conjunction with customer and other contextual data in the cloud enables
precision engagement and actions to drive new revenue opportunities, costs savings and a
transformed customer experience.

CUSTOMER
9
Figure 7: Value Creation and Capture of IoT
IoT in Adaptive Case Management Scenarios
The influence of IoT on Adaptive Case Management scenarios is easy to see. The confluence
of the disruptive technologies of the mobile internet, cloud computing, IoT and the
automation of knowledge work is a key enabler in evolution of Adaptive Case Management.
IoT relies on cost-effective and ubiquitous mobile connectivity to devices plus cloud
computing to aggregate the data and provide the enabling tools to manage, act and learn from
this machine data in a customer context. Smart, connected products are better than humans in
accurately, consistently capturing and communicating data. In turn, knowledge workers
benefit from access to new real-time insights into machine data to help them quickly react or
better yet, proactively respond to ever changing state conditions and be armed with much
better data from which to make decisions on the proper course of action. Therefore,
inefficiencies and problems are identified and fixed sooner, saving time and money while
supporting business intelligence efforts.
Specific to Adaptive Case Management, we see a host of trends and opportunities presented
by cloud computing and IoT:

CUSTOMER
10
● The new event data and contextual data brought by IoT is making case management
much more effective by arming knowledge workers with deeper and more real-time
insight
● IoT connectivity enables new methods of customer engagement and collaboration to
improve the customer experience
● The state machine model is being adopted versus linear workflow to enable more
reactive and flexible workflow (with branches and looping) based on changing data
state conditions
● Once you are wired to connected products and other data streams, the tools that
define the workflow and orchestrations are becoming business user friendly without
need of programmers
● Manual Adaptive Case Management response mechanisms that were required due to
the unpredictable nature of issues will be able to be increasingly automated based on
machine learning and predictive intelligence

CUSTOMER
11

CUSTOMER
12
Figure 8 (a,b): Leading Disruptive Technologies (McKinsey Global Institute Analysis)
There are several real-life examples of how IoT provides a more adaptive and dynamic
element.
A security company wanted to deploy an IoT solution to improve its service levels and
efficiencies. Security sensors, such as a sensor on a door or window, eventually start to fail
and result in occurrences of false alarms until they are replaced. The false alarms cause retail
stores to be evacuated, which impacts profitability and also results in substantial fines from
government agencies. The solution leveraged data from the sensors and a predictive
intelligence engine to predict with 80% confidence that a sensor was likely to fail soon.
Those predictions along with sensor and customer data were fed to a Salesforce Service Cloud
solution as cases where the operations knowledge workers reviewed the predictions and
correlated them with existing customer work orders for the same site. The cases provided the
users with new insight into the site, equipment, equipment performance, and alarm activity.
They then created new work orders for sensor replacement and combined them with other
upcoming work to be done at the same site. The goal was to help the customer avoid lost
revenue and fines while at the same time avoiding extra truck rolls and the need to reactively
address sensors after they failed.
Another example applies to a manufacturer of diesel engines for various industrial uses. The
technicians that provide support had limited visibility into machines alarms and issues and
their probable causes. As cases were raised, the technicians often had to visit the equipment
in the field and make repeat repair trips to get the right parts resulting in extended downtime,
lost revenue and an inferior customer experience. The company decided to implement an IoT
solution to enable the capture of machine data to improve the handling of reactive cases but
even better to enable proactive service. Not only did the technicians gain better data to

CUSTOMER
13
diagnose issues and ensure they had better information for a first time fix, but they were able
to perform a diagnosis remotely that prevented failures from occurring. Furthermore,
availability of machine data such as fuel levels, oil condition, soot levels and vibration
patterns enables the systemto predict issues before they occur and, froman ACM perspective,
automate knowledge worker tasks.
So where is this headed? A sea of change is underway and the IoT transformation will shape
and move entire markets. Gartner has stated “It will soon be more expensive not to have a
connected product”. It is expected that 50 billion “things” will be connected by 2020 and 1
trillion by 2035. These smart things have a lot to say about how we leverage machine data
into the cloud and deploy the millions of connected cloud applications and systems of
intelligence that will be required to better serve ever demanding customers.
While considering the need for millions of smart, connected applications to enable this
massive transformation, it’s beneficial to examine an IoT solution blueprint. There are four
primary components required to drive real business transformation from the IoT:
1) CONNECT:
Connect to the edge and ingest data streams in real-time at scale from connected
devices/sensors, social data or any other relevant feeds (e.g. weather). The key is the
ability to handle billions not millions of data elements.
2) MANAGE:
Analyze and keep relevant “fast moving” data accessible (e.g. in memory) to enable
real-time processing. Leverage ingested data in conjunction with other “slow
moving” contextual data such as a customer profile, and apply business rules and
logic to determine actions. Predictive intelligence comes into play to take real-time
predictive actions. Persist all or a subset of data for long-term storage and big data
analytics as desired. Leverage contextual IoT apps to manage the connected product
assets and provide operational interfaces.
3) ACT:
Leverage business engines and systems of engagement (e.g. CRM systems) to take
intelligent and/or personalized actions. Actions could be opening a case, creating a
sales opportunity, pitching a real-time marketing offer, or reaching back out to the
connected device in question or even another device (M2M) to execute a command.
4) LEARN:
Leverage historical data, machine learning, and ultimately predictive intelligence to
further improve business processes, the intelligence of actions and drive new
business insights. From service processes to marketing and sales to product
management, the power of the connected data provided by the IoT coupled with an
IoT system that can manage, act and learn from it will drive immeasurable business
value.

CUSTOMER
14
Figure 9: Example IoT Platform Blueprint
The value of smart, connected products and the supporting IoT applications grows as more
products and more systems are interconnected. Products can talk to one another and
supporting applications are unified or otherwise integrated. The level of intelligence moves
from reactive to proactive to predictive. Lastly, the enterprise systems of engagement and
intelligence are integrated among themselves with other enterprise and 3rd party systems to
raise the level of intelligence and enables seamless operations and customer experiences. The
value is further increased by the network effect though deep interconnections across
companies and customers. The result is businesses are transformed and new business models
are enabled. Prepare for the rise of the machines.

CUSTOMER
15
Figure 10: Value Growth for Smart, Connected Products
For examples of IoT in action there are example Case Studies at:
http://www.thingworx.com/Case-Studies
And there is an example videos at:
https://www.youtube.com/watch?v=OlE5N-wOBWM
https://www.youtube.com/watch?v=ftDDYmJPSYI
https://drive.google.com/a/salesforce.com/file/d/0B86PcdRKALi1ZmdJUjJQMjVjeEE/view
COGNITIVE LEARNINGAND NEURAL CHAT (SHERRY COMES,GENPACT)
Smarter and More Predictive Capabilities Driving Lean Digital
(sm) Value
There is a huge shift in the expectations of IT operations, which is that companies want
business value from innovation that results in smarter, more predictive, and more efficient
operations. Companies also want the ability to analyze and score large amounts of real-time
data, while also gaining visibility into the pipeline of future innovations. Intelligent
Operations that include Predictive Analytics, Machine Learning, and Artificial Intelligence
are all new capabilities that if implemented well, can drive significant efficiencies and
improve customer experience which in turn improves business value. This trend can be seen
by Gartner’s 2016 top ten predictions:

CUSTOMER
16
Predictive analytics is the branch of data mining concerned with the prediction of future
probabilities, outcomes and trends. Machine learning is a type of artificial intelligence that
gives computers the ability to make predictions and gain insight from data. Predictions get
better as additional data is fed into the system, without (or with limited) need any human
intervention. A range of analytics based innovations are benefiting from machine learning
across back office, client interaction, compliance etc.
Artificial intelligence (AI) is the intelligence exhibited by machines or software. It is also
the name of the academic field of study which studies how to create computers and
computer software that are capable of intelligent behavior.
“Thanks to Cognitive Sciences we are now able to embed empathy, patience and
quick learning into our solutions to unlock insight from data in our pursuit of
unlimited knowledge. Robots may soon prove to be sensitive enough to become
virtual friends, assistants or chat mates. The future is actually here at Genpact
where we are chatting via Neural Chat (sm) and leveraging Intelligent Assistant’s
through Genpact’s Intelligent Assistant (sm).”- Chirag Srivastava, Genpact Core
Cognitive Team
There are two real-life applications of these capabilities to Adaptive Case Management
scenarios: Neural Chat (sm) and Genpact Cognitive Operations (sm).
Neural Chat with Cognitive Operations
Neural Chat adds ever increasing efficiencies in Adaptive Case Management scenarios by
combining the best of humans and machines together to satisfy a customer's needs and wants.
This leverages cognitive operations based on machine learning algorithms that can learn from
and make predictions using both structured and unstructured data without relying on rules -
based programming. One of the ways this helps is in the financial services space where more
effective analysis of the increased volume and complexity of financial information available
today allows Banking, Financial Services, and Insurance industries gain valuable insight from
data. Cognitive operations enables data scientists to train computers to solve real world
problems without requiring human assistance, as well as allow humans to leverage Intelligent
Assistants to improve outcomes of whatever they might be trying to accomplish.
Imagine just one of our customers with over 2,000 order managers in our contact center now
having real-time access, via the chat channel, to the smartest, most experienced Subject
Matter Experts (SME), 24 X 7, that is always polite, never forgets, knows the answer before
you ask the question and continually improves over time. Now they’ll have expert Q&A
access to this "knowledge garden" of information that is continually updated real-time with
complex, structured and unstructured private, public and social information and is accessible
through natural language queries.
Now imagine if the work that these order managers are doing is repetitive and/or involves
predictable operations that can be easily accomplished through Intelligent Cognitive
Operations leveraging robotic process automation, analytics and cognitive computing. We are
creating the smartest assistant in the contact center, or the smartest knowledge worker in the
middle and back office and giving them access to digital technologies, including cognitive,
analytics, and natural language queries to do their job. We are taking this highly repetitive and

CUSTOMER
17
predictable work away from the contact center agent and pushing this off to self-service, via
“chatbots” and only allowing the higher cognitive work to come through to the human who
collaborates with the Genpact Intelligent Assistant (GIA) sm to deliver their job with
excellence.
Figure 11: Genpact Intelligent Assistant(sm)
“We have invested heavily leveraging our customer and industry best practices and
experiences in bringing the concept of an Intelligent Agent for Adaptive Case
Management use cases. This Journey Map of Genpact Intelligent Assistant(sm)
represents how we are able to improve the journey a customer makes when
interacting with our contact centers.” -Vikas Mehta, Genpact Digital Integration
Services
Our focus is on not only on creating the most intelligent virtual assistant in the contact center,
but allowing contact center workers the ability to collaborate with this intelligent digital
assistant in order to make them smarter, faster, more productive and in the end, happier.
We are creating the smartest agent in the contact center, or the smartest knowledge worker in
the middle and back office and giving them access to digital technologies, including
cognitive, analytics, and natural language queries to do their job.

CUSTOMER
18
Figure 12: As-Is Traditional Chat
Traditional Chat interactions are siloed interactions with an agent and don’t allow for a 360-
degree of the customer. The traditional interactions also don’t meet the high expectations of
today's customer, who demands fast and personalized service that continually builds upon the
customer’s narrative which is their history or journey. Additionally, inefficiencies in this
traditional process add to operational costs and waste in resources.
Figure 13: Introduction of Neural Chat
With Neural Chat(sm) we add and Intelligent Cognitive Operations that will greatly increase
efficiencies in serving the customer. This also enables a much more holistic (360-degree)
understanding of the customer to better respond to the customer’s needs and specific

CUSTOMER
19
situations. Added to this is the capability to both predict, learn, and crowdsource to produce
increasingly better outcomes.
Figure 14: Neural Chat Process Flow
Using our Lean Digital approach, we established the Neural Chat process flow that would best
govern the interactions with the customer while establishing the required systemcapabilities.

CUSTOMER
20
Figure 15: Example Neural Chat Interaction
Augmenting the Agent’s customer service skills with not just information, but also machine
learned capabilities provides a leap in service to the customer.

CUSTOMER
21
Figure 16: Potential Future Contact Center
As the combination of human agent and machine learning evolves, it takes customer self-
service to the next level. The potential for a truly omnichannel personalized experience with
a 360-degree understanding of the customer is possible.
“Cognitive science is a significant step in the human journey towards decoding
artificial intelligence. Cognitive solutions drive transformational business value
across the end-to-end value chain. Genpact is building Cognitive solutions as a
service and applying these cognitive technologies to transform mid-office and back-
office operations known as Genpact Cognitive Operations.”- Prhabhu Srinivasan,
Genpact Core Cognitive Team
By leveraging our Intelligent Cognitive Operations via Neural Chat the following business
values would be unlocked:
● Reduce the average handling time
● Increase next enquiry prevention
● Reduce channel hand-offs
● Reduce staff turnover rate
● Reduce time on chat
● Increase customer satisfaction
● Reduce post-call processing

CUSTOMER
22
● Reduce training cost
● Reduce supervisory time
● Increase staff able to handle multiple standard operating procedures
● Reduce agent-to-agent transfer
● Decrease likelihood of contacts
● Decrease likelihood of contacts
● Increase quality and consistency
● Increase ability to quickly put in new regulations and procedures
● Reduce error rates
● Provide the ability to have full traceability and auditability
Risks
As with all new technologies, there are risks that have to be addressed with proper planning
and governance. The Axiom “Garbage-In Garbage-Out” is valid. For example a chatbot (Tay
AI) developed by Microsoft went rogue on Twitter on March 24, 2016, swearing and making
racist remarks and inflammatory political statements. Just 24 hours after release, Microsoft
had to terminate the program.
With proper governance, controls, and human expert guidance this type of scenario can be
avoided.
CONCLUSIONS
The Age of the Customer is forcing an accelerated convergence of technology capabilities to
bring a customer-centric 360-degree experience. The market is forcing us to bring together
People, Process, Information, and Technology in new ways exponentially faster. Traditional
on-premise only Architectures can’t keep up with the pace of change. The introduction of
cloud capabilities has enabled hybrid Modern Architectures to accelerate applications and
services all while effectively managing budgets.
The next generation applications combine traditional workflow, business processes, and
adaptive case management use cases with new capabilities in cloud, mobile, social, IoT, and
Artificial Intelligence. For example: Gartner predicts the Nexus of Forces (cloud, mobile,
social and big data) is moving us to this “post app era.”
Modern Cloud Architectures is driving the future of Adaptive Case Management for the Age
of the Customer. The Modern Architecture “Fabrics” allow the combination of both existing
and new technologies, specifically cloud technologies. We have focused on how the three
key areas (Social/Collaboration/Communities, IoT, and Artificial Intelligence) are driving
new Adaptive Case Management use cases being demanded by the market in the Age of the
Customer.
REFERENCES
Salesforce1-Platform-Services-ebook:
https://secure2.sfdcstatic.com/assets/pdf/misc/Salesforce1-Platform-Services-ebook.pdf
http://www.forbes.com/sites/jimblasingame/2014/01/27/its-the-age-of-the-customer-are-you-
ready/#645a8df65324

CUSTOMER
23
http://www.wsj.com/articles/cios-face-the-age-of-the-customer-1423540849
Winning In The Age Of The Customer
by Michael E. Gazala, April 6, 2015; Forrester Research
http://www.wsj.com/articles/microsoft-muzzles-its-artificially-intelligent-twitter-persona-
1458843873?mod=rss_Technology
The Rise of SYSTEMS OF INTELLIGENCE How The Internet of Things and smart systems
will change everything, Salesforce IoT Cloud
(Gordon Hui,JULY 29, 2014)
https://hbr.org/2014/07/how-the-internet-of-things-changes-business-models
(H. James WilsonBaiju ShahBrian Whipple, OCTOBER 28, 2015)
https://hbr.org/2015/10/how-people-are-actually-using-the-internet-of-things
(Industrial Internet Consortium, 2015-06-04) Industrial Internet Reference Architecture
http://www.iiconsortium.org/IIRA-1-7-ajs.pdf
http://blogs.forrester.com/diane_clarkson/10-04-06-
do_your_customers_want_telephone_you_service
http://www.ns.umich.edu/new/releases/20192-firms-own-social-networks-better-for-business-
than-facebook
http://www.genpact.com/docs/default-source/resource-/process-automation-circa-2015
http://www.mckinsey.com/business-functions/business-technology/our-insights/disruptive-
technologies
https://billhubbell.wordpress.com/2013/07/02/12-disruptive-technologies-mckinsey-global-
institute/
http://fortune.com/2016/04/07/salesforce-exec-ai-service/
http://www.salesforce.com/platform/products/thunder/
http://www.itworldcanada.com/article/gartner-top-ten-predictions-for-2016-and-post-app-
era/377594
Smart Connected Products e-Book (PTC, 2014)

ACMPaperFinalDraft.docx (5)

Recomendados

Recomendados

Más contenido relacionado

La actualidad más candente

La actualidad más candente (19)

Similar a ACMPaperFinalDraft.docx (5)

Similar a ACMPaperFinalDraft.docx (5) (20)

ACMPaperFinalDraft.docx (5)