MODIHOST: AI powered Blockchain enabled Next Generation HMS€¦ · Customer Experience Lifecycle 09 BUY STAY DEPART MARKET & ATTRACT SERVE & DELIGHT SERVE BOOK 4 EVALUATE OFFER 3

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


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


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


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


Find out more

Compare

Commit

Activity

Web, Mobile, Call,

Chatbot/NLP, Social

Web, Mobile, Call,

Chatbot/NLP, Social

Web, Mobile, Call,

Chatbot/NLP, Social


Chatbot/NLP

Channel

Ads for provider XaaS, context driven query, 360°

customer data – personalized o�ers, loyalty cross-linkage,





and honest view



HMS PlayCriterion

Price, Personal

Preferences,

Location proximity



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


Find out more

Compare

Commit

Activity

Web, Mobile, Call,

Chatbot/NLP, Social

Web, Mobile, Call,

Chatbot/NLP, Social

Web, Mobile, Call,

Chatbot/NLP, Social


Chatbot/NLP

Channel

Ads for provider XaaS, context driven query, 360






and honest view



HMS PlayCriterion

Price, Preferences,

location proximity



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


Find out more

Compare

Commit

Activity

Web, Mobile, Call,

Chatbot/NLP, Social

Web, Mobile, Call,

Chatbot/NLP, Social

Web, Mobile, Call,

Chatbot/NLP, Social


Chatbot/NLP

Channel

Ads for provider XaaS, context driven query, 360






and honest view



HMS PlayCriterion

Price, Preferences,

location proximity



The best option

15HMS Core through Stay cycle

STAY

5

6

7

8

Number

Arrive & Check-in

Serve

Depart

Refer

Phase

Welcome, Transport


Goodbye, Transport

Refer others

Activity


Chatbot, NLP


In-person, Call

Mobile Chatbot/NLP,

In-person, Call


Channel


360 data, Loyalty programs




IoT sensor data

XaaS: Survey, Referral Bonus / Incentives,

Paint point / CX capture, feedback, verify

HMS PlayCriterion

Guest Status,

Type of Booking

Facilities, Info,


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


Goodbye, Transport

Refer others

Activity


Chatbot, NLP


In-person, Call

Mobile Chatbot/NLP,

In-person, Call


Channel


360° data, Loyalty programs




IoT sensor data



HMS PlayCriterion

Guest Status,

Type of Booking

Facilities, Info,


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


Goodbye, Transport

Refer others

Activity


Chatbot, NLP


In-person, Call

Mobile Chatbot/NLP,

In-person, Call


Channel


360° data, Loyalty programs




IoT sensor data



HMS PlayCriterion

Guest Status,

Type of Booking

Facilities, Info,


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


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


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


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


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


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


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


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)


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)

Documents

MODIHOST: AI powered Blockchain enabled Next Generation HMS€¦ · Customer Experience Lifecycle 09 BUY STAY DEPART MARKET & ATTRACT SERVE & DELIGHT SERVE BOOK 4 EVALUATE OFFER 3