MODIHOST:Next Generation HMS
Ver. 1.0 | October 2019
TECHNICAL WHITEPAPER
AI powered
Blockchain enabled
End customer experience centered
Big data & analytics leveraged
Service provider focused
The Next GenerationHotel Management System
MODIHOST TECHNICAL WHITEPAPER
Modihost Core HMS Technical Whitepaper 03
Motivation, Vision, Theme, High-level outline of the use cases, and grouping of use cases by the customer life cycle
High level architecture for group of use cases, and categorization by technology (AI, IoT, Microservices)
Architecture for HMS
Technology selection and rational for use case realization
Analytics categorization by personalization and generalization
High-level architecture for recommendation engine and NBA/NBO
AI, Analytics, IoT, Big Data interactions
Architecture Realization Roadmap for the HMS platform based on Microservices approach
AgendaTHE NEXT GENERATIONHOTEL MANAGEMENT SYSTEM
04
Stability is no more for granted – it was a luxury of
the past. Advances in technology led by ubiquitous
connectivity, concern for the climate change,
increasing awareness, access to information, and
integration of culture have fundamentally shifted the
market dynamics. These shifts are causing disruptions
and globalization at an unprecedented pace.
In today’s environment, only a cognitive enterprise
can thrive. The one that is agile enough to learn from
its mistakes and self-corrects itself. The one that
intelligently interacts with its clients, customers, and
their environment in a manner that it adapts to exactly
what they need and delivers it to their delight, paying
Aggarwal A, Jindal DExcerpts from ‘Data driven AI’
particular attention to speci�c requirements of each
one of them individually. The next generation platform
to support a cognitive enterprise must have the
customer at its center and be focused on meeting their
needs. As these needs change, the platform must
enable the cognitive enterprise to reinvent itself. This
reinvention must ripple through the entire
organization across people, culture, technology, skills
and processes, to quickly renew and readjust.
Innovative adaptation must be engineered into very
foundation of the enterprise itself as well as into
enabling platform, with mechanisms of �exibility to
auto-scale across a multitude of dimensions.
Modihost Core HMS Technical Whitepaper
MotivationTHE NEXT GENERATIONHOTEL MANAGEMENT SYSTEM
05
for interactive communication
to provide outstanding service
in real-time, setting the new
standard in hospitality
for interactive communication
to provide outstanding service
in real-time, setting the new
standard in hospitality
FUTURISTIC CUSTOMEREXPERIENCE PLATFORM
Modihost Core HMS Technical Whitepaper
VisionTHE NEXT GENERATIONHOTEL MANAGEMENT SYSTEM
06
To create an innovative
Microservices based core HMS
System with value added services
leveraging cloud, AI/ML, NLP,
Blockchain, IoT, and state of the
art in technology to bring a
differentiated customer
experience and generate new
revenue streams for our clients
To create an innovative
Microservices based core HMS
System with value added services
leveraging cloud, AI/ML, NLP,
Blockchain, IoT, and state of the
art in technology to bring a
differentiated customer
experience and generate new
revenue streams for our clients
Modihost Core HMS Technical Whitepaper
MissionTHE NEXT GENERATIONHOTEL MANAGEMENT SYSTEMTHE NEXT GENERATIONHOTEL MANAGEMENT SYSTEMTHE NEXT GENERATIONHOTEL MANAGEMENT SYSTEMTHE NEXT GENERATIONHOTEL MANAGEMENT SYSTEM
07
Creating a di�erentiated experience for the customer and real net new value for the service provider
Based HMS, AI powered and blockchain enabled services – all o�ered on a pay by usage ‘XaaS’ model
Delighting the customer while creating new revenue streams and additional cross-sell / up-sell opportunities for interested customers in a non-intrusive and non-annoying manner
Modihost Core HMS Technical Whitepaper
ThemeTHE NEXT GENERATIONHOTEL MANAGEMENT SYSTEM
EXPERIENCE MICROSERVICES
08Modihost Core HMS Technical Whitepaper
Core HMS enables looking, dynamic pricing, selection, inventory hold, booking, con�rmation, and related services
Value added HMS provides AI powered and blockchain enabled services, big data & analytics, recommendations for next best o�er / next best action
BOTH CORE AND VALUE-ADDED HMS ARE OFFERED ON A PAY BY USAGE ‘XAAS’ MODEL
HMS and Customer Experience Use Cases
Defining the new threshold for end to end customer interaction and experience
THE NEXT GENERATIONHOTEL MANAGEMENT SYSTEMTHE NEXT GENERATIONHOTEL MANAGEMENT SYSTEMTHE NEXT GENERATIONHOTEL MANAGEMENT SYSTEMTHE NEXT GENERATIONHOTEL MANAGEMENT SYSTEM
09Customer Experience Lifecycle
BUY STAY
DEPARTDEPART
MARKET & ATTRACTMARKET & ATTRACT SERVE & DELIGHTSERVE & DELIGHT
SERVESERVE
BOOKBOOK
4
EVALUATE
OFFER
EVALUATE
OFFER3
LOOK /
EXPLORE
LOOK /
EXPLORE
1
EDUCATE /
LEARN
EDUCATE /
LEARN2
REFERREFER
8
7
ARRIVE &
CHECK-IN
ARRIVE &
CHECK-IN
5
6
360º View of
Customer
Omni-Channel
& Multiplatform
Access
Sales & Service
Management
10HMS Experience — Value Proposition for providers / Customers
ACQUISITIONACQUISITION
New Markets &
Lead Management
Account & Contact
Data Enrichment
Predictive Analytics
COST SAVINGSCOST SAVINGS
Work�ow Automation
Internal Collaboration
Single Source
of Information
RETENTIONRETENTION
Omni-channel
Case Management
Work�ow Automation
to Support Improved
Customer Engagement
Delighted Customer
Experience for Repeat
Business and Referrals
Cross-business Unit Lead
Sharing for Cross/Up Sell
Collaborative
Opportunity Management
Improved Information
Sharing and Value – added
Data Enrichment
EXPANSIONEXPANSION
Personalized
attention
Personalized
attention
What I need
When I need
Where I need
What I need
When I need
Where I need
WOWTHE CUSTOMER
FOUNDATIONALFOUNDATIONALGovernance
& Change
Management
Standard
Reporting &
Analytics
11
1
2
3
4
5
6
7
8
Number
Look / Explore
Educate / Learn
Evaluate O�ers
Book
Arrive & Check-in
Serve
Depart
Refer
Phase
Browse, gather inputs
Find out more
Compare
Commit
Welcome, Transport
In-room service, upkeep
Goodbye, Transport
Refer others
Activity
Web, Mobile, Call,
Chatbot/NLP, Social
Web, Mobile, Call,
Chatbot/NLP, Social
Web, Mobile, Call,
Chatbot/NLP, Social
Web, Mobile, Call, Email,
Chatbot/NLP
Mobile, GPS, In-person,
Chatbot, NLP
Text, Email, Chatbot/NLP,
In-person, Call
Mobile Chatbot/NLP,
In-person, Call
Text, Call, Email, Social
Channel
Ads for provider XaaS, context driven query, 360°
customer data - personalized o�ers, loyalty cross-linkage,
dynamic pricing engine, recommendation engine
Provide more details per context, more
granular personalization, best o�ers
Comparison engine, ratings, at a glance fair
and honest view
CPQ, Order Management System,
Inventory Interaction XaaS, CCTx,
Extra Services, Add-ons, Preferences,
360 data, Loyalty programs
Mobile app chatbot – reschedule, weather, event
cancellations, interactions, preferences, menu, orders, IoT
Billing, Charges veri�cation & dispute settlement,
IoT sensor data
XaaS: Survey, Referral Incentives,
Pain point / CX capture, feedback
HMS PlayCriterion
Price, Preferences,
Location proximity
Facilities, Attractions
Suitability to needs
The best option
Facilities, Info,
Concierge, Environment
Ease of checkout,
Bill delivery
Wowed
Guest Status,
Type of Booking
Customer Experience Lifecycle phases at a glance
BUY
STAY
12HMS Core through Buy cycle
BUY
Swag List of XaaS:
1. Drives
2. Ads for provider/s, subscribed-in options, comparison of discounts from other providers, direct sales
incentive, context driven query, device IP correlation, 360 customer data capture, preferences capture,
retrieval – personalized o�ers (dynamic recommendation engine ingests big data from social channels
in real time, loyalty cross-linkage, dynamic pricing engine, NBO/NBA (this is the most important phase
where a provider had a �rst chance to attract attention of the explorer buyer – so match what one needs
wisely to what you o�er: internally score options before recommending)
3. Comparison Engine (within facility / brand), Cross-brand, Cross-type comparisons by context, ratings
from review / multiple / averaged scores (this phase is comparing and evaluating selections before
�nal decision)
4. CPQ, Order Management System, Inventory Interaction, CCTx, Commit Tx, Con�rmation through
preferred channels – email, chat, sms text, with GPS directions / coordinate details, location and
weather warnings
1
2
3
4
Number
Look / Explore
Educate / Learn
Evaluate O�ers
Book
Phase
Browse, gather inputs
Find out more
Compare
Commit
Activity
Web, Mobile, Call,
Chatbot/NLP, Social
Web, Mobile, Call,
Chatbot/NLP, Social
Web, Mobile, Call,
Chatbot/NLP, Social
Web, Mobile, Call, Email,
Chatbot/NLP
Channel
Ads for provider XaaS, context driven query, 360°
customer data – personalized o�ers, loyalty cross-linkage,
dynamic pricing engine, recommendation engine
Provide more details per context, more
granular personalization, best o�ers
Comparison engine, ratings, at a glance fair
and honest view
CPQ, Order Management System,
Inventory Interaction XaaS, CCTx,
HMS PlayCriterion
Price, Personal
Preferences,
Location proximity
Facilities, Attractions
Suitability to needs
The best option
13Value Added HMS through Buy cycle
BUY
Swag List of VAaaS:
1 & 2. Reinforcement learning (AI) driven Ads for provider/s (ads that evaluate e�ectiveness of previous ad
actions that converted to buys), Reinforcement learning driven comparison of other providers
(comparisons that have e�ectively been considered previously by same buyer or buyers of similar interest
pro�le), AI layer assisted context driven query mapping to multiple data sources, AI assisted personalized
recommendations (reinforcement learning to value add), AI driven pricing (reinforcement learning)
3. Context driven, AI assisted (reinforcement learning) comparison engine enablement (within facility /
brand), Cross-brand,
4. Chatbot assistance to enable booking and provide conformation Chatbots also enable 1,2 & 3
1
2
3
4
Number
Look / Explore
Educate / Learn
Evaluate O�ers
Book
Phase
Browse, gather inputs
Find out more
Compare
Commit
Activity
Web, Mobile, Call,
Chatbot/NLP, Social
Web, Mobile, Call,
Chatbot/NLP, Social
Web, Mobile, Call,
Chatbot/NLP, Social
Web, Mobile, Call, Email,
Chatbot/NLP
Channel
Ads for provider XaaS, context driven query, 360
customer data – personalized o�ers, loyalty cross-linkage,
dynamic pricing engine, recommendation engine
Provide more details per context, more
granular personalization, best o�ers
Comparison engine, ratings, at a glance fair
and honest view
CPQ, Order Management System,
Inventory Interaction XaaS, CCTx,
HMS PlayCriterion
Price, Preferences,
location proximity
Facilities, Attractions
Suitability to needs
The best option
14Analytics HMS through Buy cycle
BUY
Swag List of AaaS:
Generalization:
Corelate from device ID the browsing history, looks and books and map to just gathered data on customer
demographics and generic preferences to aggregate the most likely o�ers to be accepted (Step 1)
Personalization:
Further re�ne output from Step 1 above to laser beam the focus on this particular individual, in view of
personal tastes and preferences, and immediate correlation with any additional inputs from social media
and other applicable data sources / rules (if any, viz. speci�c corporate restrictions for rate cap in case of
business travelers)
1
2
3
4
Number
Look / Explore
Educate / Learn
Evaluate O�ers
Book
Phase
Browse, gather inputs
Find out more
Compare
Commit
Activity
Web, Mobile, Call,
Chatbot/NLP, Social
Web, Mobile, Call,
Chatbot/NLP, Social
Web, Mobile, Call,
Chatbot/NLP, Social
Web, Mobile, Call, Email,
Chatbot/NLP
Channel
Ads for provider XaaS, context driven query, 360
customer data – personalized o�ers, loyalty cross-linkage,
dynamic pricing engine, recommendation engine
Provide more details per context, more
granular personalization, best o�ers
Comparison engine, ratings, at a glance fair
and honest view
CPQ, Order Management System,
Inventory Interaction XaaS, CCTx,
HMS PlayCriterion
Price, Preferences,
location proximity
Facilities, Attractions
Suitability to needs
The best option
15HMS Core through Stay cycle
STAY
5
6
7
8
Number
Arrive & Check-in
Serve
Depart
Refer
Phase
Welcome, Transport
In-room service, upkeep
Goodbye, Transport
Refer others
Activity
Mobile, GPS, In-person,
Chatbot, NLP
Text, Email, Chatbot/NLP,
In-person, Call
Mobile Chatbot/NLP,
In-person, Call
Text, Call, Email, Social
Channel
Extra Services, Add-ons, Preferences,
360 data, Loyalty programs
Mobile app chatbot – reschedule, weather, event
cancellations, interactions, preferences, menu, orders, IoT
Billing, Charges veri�cation & dispute settlement,
IoT sensor data
XaaS: Survey, Referral Bonus / Incentives,
Paint point / CX capture, feedback, verify
HMS PlayCriterion
Guest Status,
Type of Booking
Facilities, Info,
Concierge, Environment
Ease of checkout,
Bill delivery
Wowed
Swag List of XaaS:
5. Welcome aaS – book car, driver meets and greets at airport with name display; send GPS directions via
email or mobile app, Room assignment by status, preferences (view, �oor level, road noise sensitivity);
check-in check-list by guest (personalized)
6. Check with guest that everything is �ne, and ask them to let you know if anything can be made better by
email, mobile app; Monitor and alert if tra�c jams, event cancellations or area blockage owing to political
unrest, protests, safety / severe weather
7. Thank you note by email / mobile app, bill delivery by email / preferred channel, airport transport
vehicle driver meet and greet, GPS directions to airport if self-driving a rental vehicle and warning
to adjust departure if tra�c / weather delays, �ight status noti�cation, readjust airport pickup if �ight
delayed, coordinate �ights departure time and vehicle pickup, assist in �ight rescheduling / rebooking
if signi�cantly delayed or cancelled
8. Send survey, ask to refer if satis�ed, ask for pain points and inform property / brand what they
can improve, share feedback with brand, reassure, capture CX and enrich data
16Value Added HMS through Stay cycle
STAY
5
6
7
8
Number
Arrive & Check-in
Serve
Depart
Refer
Phase
Welcome, Transport
In-room service, upkeep
Goodbye, Transport
Refer others
Activity
Mobile, GPS, In-person,
Chatbot, NLP
Text, Email, Chatbot/NLP,
In-person, Call
Mobile Chatbot/NLP,
In-person, Call
Text, Call, Email, Social
Channel
Extra Services, Add-ons, Preferences,
360° data, Loyalty programs
Mobile app chatbot – reschedule, weather, event
cancellations, interactions, preferences, menu, orders, IoT
Billing, Charges veri�cation & dispute settlement,
IoT sensor data
XaaS: Survey, Referral Bonus / Incentives,
Paint point / CX capture, feedback, verify
HMS PlayCriterion
Guest Status,
Type of Booking
Facilities, Info,
Concierge, Environment
Ease of checkout,
Bill delivery
Wowed
Swag List of VAaaS:
5. Mobile app / Robot welcomes by location tracking on arrival, auto check-in, step by step guidance to
navigate to room location, auto-o�er luggage assistance with drop instructions, auto-o�er valet parking /
self-parking with guided instructions, GPS integration for required VAaaSs.
6. IoT sensors detect what is missing and housekeeping replenishes (except when DND); Chatbot / NLP
to check everything is OK, turn lights on/o�, adjust temperature heat/cool; order in-room service.
Auto-laundry pickup; o�er spa / other services per preference and persona type without being annoying,
set or disable or readjust alarms, pick up vehicle timing adjustment, in-room breakfast delivery, set
preferred music notes (if required), provide info about facilities on the house and extra services available,
when asked, like trips to attractions and adventures etc., any special local event or occasion
(viz. President House lit up on Jan 26th in New Delhi, India)
7, 8. Personally thank (chatbot / NLP / app) for the stay and business, with request / incentive to come back
17Analytics HMS through Stay Cycle
STAY
5
6
7
8
Number
Arrive & Check-in
Serve
Depart
Refer
Phase
Welcome, Transport
In-room service, upkeep
Goodbye, Transport
Refer others
Activity
Mobile, GPS, In-person,
Chatbot, NLP
Text, Email, Chatbot/NLP,
In-person, Call
Mobile Chatbot/NLP,
In-person, Call
Text, Call, Email, Social
Channel
Extra Services, Add-ons, Preferences,
360° data, Loyalty programs
Mobile app chatbot – reschedule, weather, event
cancellations, interactions, preferences, menu, orders, IoT
Billing, Charges veri�cation & dispute settlement,
IoT sensor data
XaaS: Survey, Referral Bonus / Incentives,
Paint point / CX capture, feedback, verify
HMS PlayCriterion
Guest Status,
Type of Booking
Facilities, Info,
Concierge, Environment
Ease of checkout,
Bill delivery
Wowed
Swag List of AaaS:
Generalization (CX):
Capture data related to the customer to analyze buying patterns for services, preferences, activities
engaged (viz. adventure, tours etc.) at an aggregate level by demographics, income level, type pf traveler
(leisure, adventure, business, family) – and play back from this aggregation as needed (Step 1)
Personalization (CX): Further capture data related to the individual customer to make it 360° view, over and
above Step 1 above and play back from it as needed (Step 2)
Generalization (BX):
Capture data related to the brand to analyze customer buying patterns for services, preferences,
activities engaged (viz. adventure, tours etc.) at an aggregate level by brand type
Personalization (PX):
Further capture data related to the speci�c property to make it 360 degree view, over and above brand
aggregate level and play back from it as needed to customers when required
Use Cases to AI DialogMapping at a glance
MODIHOST TECHNICAL WHITEPAPER
I am looking for a family adventure vacation
What sort of budget are we looking at for an all-inclusive package?
19Buy: HMS AI Assist Dialog / NLP
Chats HMS AI Assistant
What sort of budget are we looking at for an all-inclusive package?
16:00
We can do Bahamas with Cruise for 10.5, Puerto Rico adventures for 12, and Big Island for 17 or Honolulu for 13 .
16:06
Chats HMS AI Assistant
Maybe..16:08
Sounds interesting16:10
Yes, go ahead16:12
Shall I book and you have within 24 hours to look at details and cancel at no cost
16:11
Volcano live view, snorkeling, scuba diving, resort for 4 nights, camping 6 nights, green sand and lava beaches, Honu turtles, complete island tour
16:09
Tell me details about Big Island16:08
Done, sent details by email16:13
Are we able to stretch a bit?16:06
Yes, all 4 of us, and between 10 to 15k16:05
And is everyone traveling?16:00
I am looking for a family adventure vacation to Hawaii or Caribbean between Dec 5 and 19 — what options are there?
15:58
Modihost Core HMS Technical Whitepaper
Pro�le data includes departure airport,
preferred airline / hotel chains / brands
HMS AI Assist Dialog / NLP(Behind the scenes)
1-2 LOOK/EXPLORE
User downloads HMS AI app, creates
family pro�le, enters credit card details,
and enables NLP feature
User downloads HMS AI app, creates
family pro�le, enters credit card details,
and enables NLP feature
CUSTOMER
Intelligent interpreter quickly identi�es
missing details and asks to �ll the gaps – once
data is completed, match general data to
search, and then further personalize options
Intelligent interpreter quickly identi�es
missing details and asks to �ll the gaps – once
data is completed, match general data to
search, and then further personalize options
HMS AI MOBILE APPVIRTUAL AGENT
20
What sort of budget are we looking at for an all-inclusive package?
16:00
We can do Bahamas with Cruise for 10.5, Puerto Rico adventures for 12, and Big Island for 17 or Honolulu for 13 .
16:06
Are we able to stretch a bit?16:06
Yes, all 4 of us, and between 10 to 15k16:05
And is everyone traveling?16:00
I am looking for a family adventure vacation to Hawaii or Caribbean between Dec 5 and 19 — what options are there?
15:58
21Modihost Core HMS Technical Whitepaper
HMS AI Assist Dialog(Behind the scenes)
3-4 EVALUATE/BOOK
Is guided through options and interest
to make desired selection
Is guided through options and interest
to make desired selection
CUSTOMER
Calls out the details gathered, and once
user commits, makes selections and makes
booking – will be auto con�rmed and
committed if user doesn’t change / cancel
within 24 hours window
Calls out the details gathered, and once
user commits, makes selections and makes
booking – will be auto con�rmed and
committed if user doesn’t change / cancel
within 24 hours window
HMS AI VIRTUAL AGENT
Maybe..16:08
Sounds interesting16:10
Yes, go ahead16:12
Shall I book and you have within 24 hours to look at details and cancel at no cost
16:11
Volcano live view, snorkeling, scuba diving, resort for 4 nights, camping 6 nights, green sand and lava beaches, Honu turtles, complete island tour
16:09
Tell me details about Big Island16:08
Done, sent details by email16:13
22Modihost Core HMS Technical Whitepaper
HMS AI Assist Dialog / NLP(Behind the scenes)
5-8 SERVE
User interacts with HMS app with voice
messages or dialog box to provide inputs,
get information, and make changes
User interacts with HMS app with voice
messages or dialog box to provide inputs,
get information, and make changes
CUSTOMER
Tracks �ight arrival to coordinate car service,
hotel auto check-in; takes inputs from dialog
and preferred menu from pro�le/s to order
dining; connects to speci�c resort’s IoT API to
adjust room temp
Tracks �ight arrival to coordinate car service,
hotel auto check-in; takes inputs from dialog
and preferred menu from pro�le/s to order
dining; connects to speci�c resort’s IoT API to
adjust room temp
HMS AI VIRTUAL AGENT
Our �ight just landed, we have checked in bags
17:05
You have been pre-checked to an Ocean view room B4321 – it will open with app
17:09
Great17:08
Room is too cold17:12
Can we get some food?17:15
Car service driver Linda will greet you as you exit to baggage carousel – Her cell is xxx-xxx-xxxx
17:06
Adjusted temperature to 7217:13
Your preferred menu?17:16
23Conventional Core HMS Architecture at a glance
Access Channel (Direct)
Access Channel (OTA)
Access Channel (Call)
Access Channel (App)
Facility Management
Reporting
Point of Sales Services
Back-o�ce
Front-desk
Property Management
(By property)
Inventory (By property)
Revenue Management
CRM (Common across brand)
Reservation (Common across
brand)
CHAN
NEL
MAN
AGEM
ENT
24Conventional Core HMS Architecture at a glance
Social / External / Other data sources
Dynamic Pricing Engine
Personal Pro�le 360° view
RFID
PERS
ONAL
ASS
ISTA
NT A
PP (H
MS
VIRT
UAL
AGEN
T)
IOT
LAYE
R IN
TEGR
ATED
WIT
H PR
OPER
TY S
YSTE
M
AI/ML LAYER FOR VALUE ADDED SERVICES
INTEGRATED ANALYTICS (GENERALIZED / PERSONALIZED)
Access Channel (Direct)
Access Channel (OTA)
Access Channel (Call)
Access Channel (App)
Facility Management
Reporting
Point of Sales Services
Back-o�ce
Front-desk
Property Management
(By property)
Inventory (By property)
Revenue Management
CRM (Common across brand)
Reservation (Common across
brand)
CHAN
NEL
MAN
AGEM
ENT
25Future HMS Solution Architecture:Target Digital HMS enabled by Microservices & APIs
B2C
CHANNELSCHANNELS
API Layer Front-end MicroservicesMessaging Framework / SPOT
APIs Back-end Microservices
AI / IoT / IA / BC VA Microservices
CRM / RM / Billing Core HMS Microservices
Data Lake
Big Data
Databases
Data Management & Governance
Data Management & Governance
B2B B2E Dealers, Partners, Vendors, Suppliers, other third parties
Legacy Enterprise / Property Applications
• Each HMS System functional module will be divided into small components based on Microservices
• Each Microservice will interface with API layer. The communication layer will be implemented using
a simple “messaging framework” instead of a more complex enterprise service bus and business
process management, as applicable.
• Data is consolidated centrally, and Information will be accessed by using standard API Layer.
• Based on this architecture, data and application layers are separated,
and information will be shared across the entire enterprise.
• Big data & analytics capabilities will be consolidated into centralized
systems and enriched with prescriptive and cognitive functionalities.
END TO END GOVERNANCE, STANDARDS, INDUSTRY BEST PRACTICES, FRAMEWORKS
KAFK
A /
ADAP
TERS
/(N
O)SQ
L
26
NETWORK / IOTNETWORK / IOT
SYSTEMS OF ENGAGEMENTSYSTEMS OF ENGAGEMENT
INTEGRATION
Inventory Management, Provisioning, Facilities Management, Back-o�ce
APIs / Microservices Management, Gateways
OMNI-CHANNEL
Experience Orchestration
Personalisation
Presentation and Access Layer Portals, Cognitive Help/Dialogues
End-State HMS Reference Architecture
END TO END DATA MANAGEMENT AND ARCHITECTURAL GOVERNANCE
Ana
lyti
cs
Aut
omat
ion
Cus
tom
er M
aste
r
O�
erin
gs C
atal
ogue
AI /
Cog
niti
ve S
ervi
ces
& S
uppo
rt
Secu
rity
and
Pri
vacy
Enf
orce
men
t
SubscriberSubscriber EnterpriseEnterprise EmployeesEmployees Agents/RetailersAgents/Retailers Casual UsersCasual Users PartnersPartners VendorsVendors
SYSTEMS OF RECORD, SYSTEMS OF INSIGHTSYSTEMS OF RECORD, SYSTEMS OF INSIGHT
CRM Pricing Billing Payments Realtime RatingRevenue / Booking Management
Procurement Self-careContext–sensitive HelpPartner Portal
Realtime / PoS O�ers
Virtual Agents
BI WFMAccounts ReceivableRealtime Analytics
Customer Insights
Next Best ActionNext Best O�er
27
Solution component blocks implementable by COTS approach or Microservices, or combination thereof
HMS solution component blocks mapped across technology layers – target state architecture deeply leverages AI / IoT for actionable insights to deliver contextual services that resonate with customer experience
IOT INTEGRATIONIOT INTEGRATION
HMS ANALYTICSHMS ANALYTICS
APPLICATIONS AND HOSPITALITY SERVICES
Solutions for HMS enterprise brand and
property business functions
AI
Cognitive building blocks
DATA
Prepare data for cognitive
CLOUD INFRASTRUCTURE
A highly scalable, security
enabled infrastructure
Facilities
Predictive Models Use Case Models
HMS Data Models – 3NF, Graph AI Driven Recommendation Engine
Data Science Experience with ML
HSM Data Collection Adaptors Transformation, Aggregation, Enrichment
Cloud Integration
Networking Security
DevOps Tooling
Object Storage File Storage
Weather Room Inventory Room Blinds
Pricing
Inventory Back-o�ce Asset ManagementVirtual Agent
Booking Billing Front O�ceMediation
LightingWFM
CRM
Room Environment
Marketing Analysis & Realtime O�ers
Cyber Security / Risk Compliance
PoS Sale / Services (Intergate through APIs)
Revenue Management
Cognitive / Integration / Micro-services
Core Enterprise Infrastructure
Virtual Servers
CognitiveSystems
Property Management
Explore and Discover
Bathroom Upkeep
Conversation
Visual Recognition
Discovery
Speech
Compare and Comply
Document Conversion
VAaaS
Natural Language Understanding
Tone Analyzer
Natural Language Classi�er
Personal Insight
NBA / NBO Recommender
API API API API API API
API API API API API API
Ingestion Storage Analytics Deployment Governance
28
Modular approach, scalable,
open, no vendor lock-in
NLP, proven on multiple
deployments
Context driven development
Ease of deployment
Extended search and price
adjustment within limit checks
Fast access, quick updates
Social, IoT, weather,
other data integration
Agile CD/CI/CT
Labeling data for training sets
using Open Source tools
RationaleCriterion
Move away from COTS
Conversational, Intelligent
Reinforced learning
Seamless integration
Dynamic pro�le updated
with big data
Unstructured data ingestion
Cloud based continuous
deployment
Reinforced learning
with outliers
Consistent results,
irrespective of data format
Technology
Microservices
Watson Assistant
AI / ML platform
API exposition
No SQL Cloud database
Hadoop / Ka�a
Docker Container /
Cloud
AI / ML platform
Annotation / Extraction
(Supervised Learning)
Scope
Core HMS Module functions
Virtual Agent
Value-added services
IoT integration
Customer Pro�le – XRM
(extended)
Data ingestion from multiple
sources / formats / emails
Big data integration
Deployment
Dynamic Pricing Engine
Technology Selection and Rationale
29Analytics enrichment by personalization and generalization of data
GENERALIZATION:GENERALIZATION: Remove all identi�ers, anonymous – white-label to sell as trends
PERSONALIZATION: Address speci�c user needs (vegan, organic, 72°, golf, hiking,..)
AI / ML LAYER: Context driven integration and enrichment
Real time update with social, VA, IoT, browsing inputs
Customer Pro�le Data (basic / extended – includes sub users)
CONTEXTEXAMPLE:
Predict Churn by demographics/ Location(Generalization);
Customer Sentiment/ Tone Analysis / Browsing behavior (Personalization)
TARGET NBA/NBO for CUSTOMER RETENTION:
Incentives by demographics/ Location(Generalization);
Speci�c incentives per XRM pro�le, personalized Issue resolution (Personalization);
Referral Bonus
UNDERSTANDUNDERSTAND
Multiple data
sources
Non-digital
inputs
The context
REASONREASON
Find
connections
Recognize
ambiguity
Considers rules
LEARNLEARN
Mistakes are not
repeated
Apply patterns
of challenges to
each situation
30
Recommender (In-memory – Analytical Model)
PersonalizationEngine
Query GenerationEngine
Geo-Campaign
App Integration Job Scheduler
GeoTargeting App / UI
Recommendation Engine:Partner/PoS Geo-Targeting Architecture – Cloud enabled
PAY-BY-USAGE, GET PAID BY END-USER BUYING
MODELS FOR CLOUD ENABLED ENVIRONMENTS
Consumer movement tracking
(local, inter-city, intra-region,
inter-national initiates data
collation request
OGC WPS*
(Consumer GeoSpacial Data),
IP Spidering, Spend/
Preference Pro�le
*OpenGIS Web Processing Service
DATA LIFECYCLE MANAGEMENT, GOVERNANCE, SECURITY SERVICES, PROCESS CONTROL
BIG DATA PLATFORM aaS
Data aaS,Integration aaS
BIG DATA PLATFORM
HIVE Hbase
Campaign delivery channels
Target device rendering
Application aaS
CROSS-SELL / UP-SELL:
Restaurant
SPA
Attractions
Shopping
Adventure
Sports
Location X
Data Caching
Source Batch Integration/
one-o�triggers
DownstreamBatch
Integration
SourceSystems
DownstreamSystems
31Cross-brand loyalty integration
POTENTIAL TO OFFER AS A
VALUE ADDITION IN LOYALTY
SUPPLY CHAIN ONCE CRITICAL
MASS HAS BEEN GATHERED
SMART CONTRACTS /
PERMISSIONED BLOCK-CHAIN: mapping to / from speci�c loyalty program
to / from Global Uni�ed Loyalty, with
options to transfer / gift points
UINas a cross-reference
identi�er integrates
all speci�c brands to
a single Global system
UIN Global Cross-Ref Identi�er
ModiHost Intelligent Platform
Customer Pro�le
GlobalUni�edLoyalty
INSURANCEHOSTEL DYNAMIC PKG
PKG TOURSHOTEL
GROUND
RENTAL CAR
GOLF RAIL
ACTIVITIES
AIR CRUISE
32AI, Analytics, IoT, Big Data interactions (Illustrative)
Adjust Room Temperature
VA taps into facility API
Request Object passed to FMS IoT interface
Room temp adjusted
Order Dinner / PoS Service
Read Profile Social Media Inputs
Evaluate Options / Preferences / Choices
(Personalize)
Purchase
Book Hotel / Flights
Read Profile Social Media Inputs
Evaluate Options / Preferences / Choices
(Personalize)
Purchase
3
3
19°
33HMS Architecture Roadmap at a glance (Quarterly)
Stea
dy
Stat
e P
hase
1
Stea
dy
Stat
e P
hase
2
Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11
Go Live at Flagship PropertyRoll out MVP Phase 1, Continue to build additional functionalities for Phase 2
Core HMS DevelopmentMicroservices for HMS functions (Brand)
Core HMS DevelopmentMicroservices for HMS functions (Property)
VAaaS HMS DevelopmentAI / ML / VA services
HMS Cognitive Analytics DevelopmentAI driven analytics and data enrichment services
HMS Cognitive Process DefinitionsOrganization, Culture, People, Technology, Business Processes
Planning, Marketing, Partner solicitationBeta site testing and integration in eco-system (Brown�eld / Green�eld)
Go Live at Partnering Brand / PropertyRoll out MVP Phase 1, Continue to build additional functionalities for Phase 2
Process TransformationComponent Business Modelling, Application Portfolio Management Enterprise Application Modernization
34Modihost Core HMS Technical Whitepaper
Flexibility in the ModiHost HMS next generation platform must accommodate a diversity of options, tastes, and preferences
From eco-tourist to luxury seeker, any tech-savvy customer must
be able to leverage inherent �exibility in the platform to customize
o�erings to their exacting needs
A multitude of options to pick across the spectrum of o�ering's
portfolio in a non-binding manner
Not a one size �ts all approach – you can go camping, hiking, on
a yoga retreat, or seek an all inclusive luxury vacation, and still better,
anything in-between that �ts your requirements, wishes, and budget
Your tastes and preferences may vary over time, and the platform
adjusts and adapts to a ‘new’ you
35Modihost Core HMS Technical Whitepaper
VAaaS:Additional optional services to be considered
Virtual tour of the room and views from the window
(dovetails to directions once inside the property)
Virtual vicinity tour and aerial view of property
Place a plant in the room – which one?
Bamboo, money-plant, others?
Speci�c dining options – vegan, vegetarian, organic
only: we can be very speci�c and deep drilling down
to any level of detailed decomposition
36
3NF (3rd Normal Form)
aaS (as a Service)
AI (Arti�cial Intelligence)
API (Application Programming Interface)
B2B (Business to Business)
B2C (Business to Customer)
B2E (Business to Enterprise)
BC (Block-Chain)
BI (Business Intelligence)
BX (Brand Experience)
CCTx (Credit Card Transaction)
CD (Continuous Development / Deployment)
CI (Continuous Integration)
COTS (Commercial O� The Shelf)
CPQ (Con�gure Price Quote)
CRM (Customer Relationship Management)
CT (Continuous Testing)
CX (Customer Experience)
DND (Do Not Disturb)
FMS (Facility Management System)
GPS (Global Positioning System)
HMS (Hotel Management System)
IA (Integrated Analytics)
IoT (Internet of Things)
IP (Internet Protocol)
k (1000)
ML (Machine Learning)
MVP (Minimum Viable Product)
NBA (Next Best Action)
NBO (Next Best O�er)
NLP (Natural Language Processing)
PMS (Property Management System)
Modihost Core HMS Technical Whitepaper
Glossary
PoS (Point of Sales)
PX (Property Experience)
RM (Revenue Management)
RoI (Return on Investment))
SQL (Structured Query Language)
TBD (To be decided)
UIN (Universal Identi�cation Number)
UNY (Universal Virtual Currency)
VA (Value Addition)
VAaaS (Value Addition as a Service)
WFM (Workforce Management System)
XaaS (Anything as a Service)
XRM (Extended Customer Relationship Management)
2019 © ModiHost
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