Customer Led Distributorship Using Data · Omni-channel Systems which can provide true omni-channel...
Transcript of Customer Led Distributorship Using Data · Omni-channel Systems which can provide true omni-channel...
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Customer Led Distributorship Using DataN i ra j Te n a nyN e t w o ve n , I n c .
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Agenda
• Current Business Environment
• Challenges and Opportunities for the Electrical Distributors
• Role of Data and Analytics
• Preparing Your Organization for Analytics
• Customer Case Studies
• Using the Microsoft Cloud for Data and Analytics
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Today’s Speaker• Co-founded Netwoven in 2001
• Held executive positions at Microsoft, Accenture, Oracle and Glaxo Smithkline
• Worked across various industries – Healthcare, Financial Services, Internet Software, and Retail
• Main focus has always been analytics with structured and unstructured data
• Frequent speaker in various industry events
• Advise clients in strategizing around Digital Transformation and Analytics
Niraj TenanyPresident and CEO
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Microsoft Cloud Company
FOUNDED IN
2001
Milpitas Boston Los Angeles Bangalore Kolkata
100+CUSTOMERS
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Cloud Infrastructure
ERP and CRM
Data and AI
Content and Collaboration
Cloud Application Development
What We Offer
Consulting
Staffing
Products
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Content & Collaboration
Data & AI
ERP & CRM
Cloud
Infrastructure
Cloud Application
Development
Consulting
• Intranet Modernization
• Governance
• eDiscovery and Litigation Hold
• Salesforce Integration
• Adoption
• Tenant Merge
• O365 Migrations
• Teams Rollout
• Data Engineering and Integration
• Data Visualization and BI
• Artificial Intelligence
• IOT
• Blockchain
• On-Prem to Online Migration
• Salesforce to Dynamics Migration
• Marketing Automation
• Sales Automation
• Integration
• Custom Development
• O365 Identity
• Productivity and Mobility
• O365 Security & Compliance
• Exchange
• Azure Apps & Services
• Managed Services
• Enterprise Mobility + Security
• Identity and Access Management
• Advanced Threat Protection
• Information Protection
• Security Management
• DLP & Encryption
• Application Migration
• Application Modernization
• Micro Services Development
• API Development
• DevOps
Consulting
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Content and Collaboration X X X X X X
Data and AI X X X X X
Cloud Application Development X X X X X
Cloud Infrastructure Management X X X X X
ERP and CRM X X X X X X
Proof of
Concept
Workshop Strategy and
Planning
Implementation
Services
Consulting
Managed
Services
Application
Maintenance
Services
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Interesting Quotes
• “When digital transformation is done right, it’s like a caterpillar turning into a butterfly, but when done wrong, all you have is a really fast caterpillar.” – MIT Research scientist
• “At least 40% of all businesses will die in the next 10 years… if they don’t figure out how to change their entire company to accommodate new technologies” – John Chambers
• “People don’t want to buy a quarter-inch drill. They want a quarter-inch hole.” –Theodore Levitt, Harvard Business School
• Be nice to nerds. Chances are that you might end up working for one – Bill Gates
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Interesting Read
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Recent Post From Linkedin
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Current Business Environment
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A World of Unprecedented ChangeAverage lifespan of a company on S&P 500
Source: Yale Professor Richard Foster
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By 2020
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Customer Engagement in the New World In the age of the customer, engagement trumps automation
Business Process Evolution
1900 1960 1990 2010
Age ofManufacturing
Age ofDistribution
Age ofInformation
Age ofCustomer
Beyond
Mass manufacturing makes industrial
powerhouses successful
Global connections and transportation systems make distribution key
Connected PCs and supply chains mean those that control information flow
dominate
a new level of customer obsession Empowered
buyers demand
Assembly Lines Supply Chains Automation Engagement
Source: Adapted from October 2013, "Competitive Advantage in the Age of the Customer", Forrester Report
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Some call it the 4th industrial revolution
Customer engagement in theNew World ….
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Who isThe DigitalCustomer?
customer experience will overtake price and
product as thekey brand differentiator
By 2020
Customer engagement in theNew World ….
Savvy using social channels.
Trusts differently than used to.
82% find peers most trusted source. [Edelman 2014 Trust Barometer]
Communicates with peers.
Communicates with companies – when ready.
Gets what they want.20% use Twitter for customer service. [Colloquy]
Social. Mobile. Local. Omni-channel.
Expects immediate response. Or nearly so.
Expects information available nearlyinstantly whensearching.
Increased velocity of consumerization of work.
Active participants in affecting change by using social networks.
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Customer Engagement in theNew World…
Macro-economic and regulatory needs
Service economyService economy is outcome-driven, partner-heavy, and lifetime-centric
Security With cloud adoption security of data in transit and rest has become key
Regulatory environment
Regulatory needs such as data residency, deep auditing, and data sovereignty play a part
Privacy Customers expect extreme personalization, but privacy is key factor in that equation
System needs
Data-driven and intelligent
Systems which are not just systems of record but can provide true insights
Omni-channel Systems which can provide true omni-channel and social is part of that
No silosSystems which are not isolated but can be orchestrated together and are flexible
Productivity-rich
Systems which focus on making employees more productive and empowered
Connecteddevices
Systems which can integrate to smart connected devices to deliver great proactive experiences
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Challenges and Opportunities for the Electrical Distributors
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Emerging TrendsDisruptive Trend Trend Overview Market Requirements
Digital Advancement
Digital transformation is a primary catalyst for new business models such as direct selling from suppliers and online via Amazon.
Targeted sales and marketing efforts are needed to help customers make more informed choices.
Technology Evolution & New Ecosystems
Increasing product innovations have resulted in the need for new supply chain ecosystems and sales approaches, diverting sales focus from initial cost reduction to operational efficiency gains.
Investing in training, certifications, and new hires is critical to stay ahead of the curve.
Countering ‘DirectSales’ Approaches
The direct-selling approach is helping manufacturers to leverage industry relationships and online engagement to cater to end customers.
To respond to such changing sales approaches, distributors will need to consider digitization of business offerings, expand their interaction with an extended value chain, and maximize wins.
Impact of B2C Industry Evolution
With the evolution within the business-to-consumer (B2C) industry, selling “customer experience” as part of the product and system sale is gaining importance.
Electrical distributors will need to promptly implement optimized eCommerce systems, advanced CRM tracking, and better warehouse automation systems to address these changes.
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Emerging Trends
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Key Customer Trends
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Building a Connected Business
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Opportunity Framework
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Role of Data and Analytics
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The world of data and Insights
Documents& Files
Mobile App Data
LogsSpreadsheets
Social Media Data
Streaming Data
Records
Azure SQL Database Business Apps
Azure Cosmos DB SQL Server
Azure SQL Datawarehouse
Streams
Azure IoT Hub Azure Stream Analytics
Azure Event HubDevice Data
Sensor Data
Your Data TodayMultiple sources and formats… and growing everyday
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The World of Data and InsightsWhy is this a new problem?
Structured Data
Web & Mobile Data Logs
Social Media Data Spreadsheets
Streaming Data IoT Data
Unstructured andSemi-Structured Data
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The 4 Vs of Data and Insights
• No ETL pipelines!
• Immediate access to data through data virtualization
• Scale-out compute for faster queries
• Spark for scale-out data prep, query, ML
Velocity
• Access all types of data –structured and unstructured in one system
• Access data from many data systems using data virtualization
Variety
• Minimize data errors in ETL pipelines by working with the data from the source
• Data is real time when you use data virtualization
Veracity
• Scalable storage in HDFS
• Feed more data to your AI through data virtualization
Volume
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New data thinking: all data has value!• All data has potential value
• Data hoarding
• No defined schema—stored in native format
• Schema is imposed and transformations are done at query time (schema-on-read).
• Apps and users interpret the data as they see fit
Store Indefinitely Analyze See ResultsGather Data
from all Sources
Iterate
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From Data on the Business, to Data is the Business
Infamous Words: “Our business is running retail stores.” -Blockbuster CEO
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MODERN BI
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Action
Value
Manual process
From data to insights andactions
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Preparing Your Organization for Analytics
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Core Focus Areas
• Customer Analytics
• Web Analytics
• Predictive AnalyticsSales Analytics
• Inventory Analytics
• Warehouse Analytics
Operational Analytics
• IOT Analytics
• Predictive Maintenance
• Safety and Risk Management
Data As A Service
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Sales Analytics• Sales Analytics
• Service Analytics
• Lead and Opportunity Analytics
• Web Analytics
• Predictive Inventory Ordering
• Warranty Management
• RMA Management
• Cross Selling
• Channel Analytics
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Sales AnalyticsCapability Current Required
Lead Management
Opportunity Management
Account Management
Territory Management
Sales Team Enablement
Insights and Analytics
Data Management
Marketing Management
No ProcessNo Automation
Some ProcessSome Automation
Some ProcessSome Automation
Full ProcessFull Automation
Some ProcessSome Automation
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Sales Analytics
PR
OSP
ECT
OP
PO
RTU
NIT
Y
CLI
ENT
KEEP CLIENT
REFER
RA
LS
CR
OSS-SELL
UP
-SELL
VIS
ITO
RS
CO
NTA
CTS
SUSP
ECT
Sales PipelineMarketing Pipeline
GrowGet Client
Building A Customer Engagement Capability Is Not A Nice To Have But A Must Have To Win And Grow Business
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Sales AnalyticsCapability Release 1 Release 2 Release 3 Release 4 Release 5 Release 6
Lead Management
Opportunity Management
Account Management
Territory Management
Sales Team Enablement
Insights and Analytics
CRM System
Marketing Automation
Community Portal
Technology (Mobile, SSO)
Data Management
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Data As A Service
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IOT AnalyticsLegacy Building Automation Systems: The Bottom-Line Impacts
Security
Over 80%of organizations worldwide experience a cyberattack every year
Legacy systems are the most vulnerable to costly DDoS attacks and breaches
Energy
30%of energy consumed by commercial buildings is wasted energy
on average, an
8% reductionin energy use saves one building
$16M/year
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IOT AnalyticsThe Real Estate Industry: A Defining Moment
+50%of all executives say that lack of familiarity with technology is a
barrier to transformation
87%of organizations admit that not transforming will impact their
ability to complete and thrive in the short term
84%of organizations recognize the
urgency to transform their legacy system to smart,
cloud-based infrastructure
55%of organizations report a
timeframe of one year or less to transform their legacy BAS
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IOT Analytics
Driving Digital TransformationAcross the Enterprise
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How to prepare yourself?
• Automate your business processes –Analytics is no good without systems and data
• Build a Data Driven Culture
• Build an analytics Center Of Excellence (COE)
• Staff the COE with skilled resources
• Data management
• Statistics, Machine Learning, Visualization
• Infrastructure and Storage
• Partner with an outside agency to fill any gaps
• Resources have both business and technology experience
• Develop a fail-fast mentality
• Delivery focused with an iterative mindset delivering projects in weeks
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What is a modern Analytical Platform?
Machine Learning, Predictive Analytics, Data Discovery and Profiling
Near Real-Time
Various Types Of Data (Structured, Unstructured, Device and Sensor)
Dynamic Scaling
Data Scientists, Data Developers, Business Analysts
Integrated Data Platform
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Roles and Skills RequiredBelow are some of the more common BI roles that exist in data, analytics, and BI departments
BI Role Responsibility Skills
BI ManagerAs the tactical leader, manages and directs the project. The BI manager must be able to communicate well and be the link between IT and business staff.
• Background in data architecting• Presentation and communication skills • PM skills • Experience with BI stack
Data ArchitectDevelops the data marts* and data warehouse architecture according to the business and technology requirements.
• Data architecting background • Data profiling • Advanced knowledge of SQL and data structures
Business Analyst Defines the requirements for the BI solution, administers the analytics experience for all users, manages data sources and access rights, and performs complex analysis and implements changes to improve organizational performance.
• Industry-specific business background • General data warehouse experience • BI background • Presentation and communication skills
ETL** DeveloperDevelops the packages that migrate data from its source location to the operational data store and the marts or warehouse.
• Programming• Deep understanding of data structures • ETL development experience
Report DeveloperOptimizes data visualization to users by creating reports and dashboards. This is a key element of a successful BI implementation.
• Programming• Expertise with data visualization • Business background preferred • Statistics understanding
Data AnalystHelps business users handle, analyze, and drive insights from the data that is within the data warehouse or data mart environment, and solve business problems by leveraging the data from the BI platform.
• Programming • Experience with data visualization development • Industry-specific business background • Background in statistics or math
Data Scientist
Conducts data-driven statistical modeling to create predictive models, analysis, and other advanced data mining and statistical tools. This is the role with the highest technical skills across the BI department. requiring skills in statistics and mathematics and a strong background in programming or scripting.
• Skills in statistics and mathematics • Background in programming or scripting • Statistical software package background• Experience with data visualization development
*A data mart is a structure/access pattern specific to data warehouse environments, used to retrieve client-facing data. The data mart is a subset of the data warehouse and is usually oriented to a specific business line or team. **Extract, transform, and load
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Customer Case Studies
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Customer Case Studies Examples
• Wineries monitoring the yield of grapes
• Wineries recommending wines based on your purchases
• Medical device companies managing the IOT data collected by devices and offering them to
• Hospitals
• Patients
• Device Manufacturers
• Online gaming companies analyzing your purchasing and playing patterns
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Using the Microsoft Cloud for Data Analytics and Artificial Intelligence
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OneDrive
for Business
Microsoft Clouds
EM+S
Suite
Dynamics 365Office 365 Azure
Yammer SharePoint Teams
Skype
for Business
Field
Service
Project
Service
Automation
Customer
Service
Finance &
Operations
Sales
Azure
Data
Lake
Azure
SQL
Azure SQL
Data
Warehouse
Azure
ML
Cortana
Analytics
Suite
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Main Technology Topics We Will Cover
• Data Analytics Platform
• Artificial Intelligence Services
• Open Data Initiative
• Platform for Rapid Applications Development
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Data Analytics Platform
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BI and AppsData-driven
Business
analytics and reporting
Power BI
Power Apps + Flow
Azure Data Services
SQL Server
AI “Accelerators”Solution
specific
AI Services and patterns
Azure Bot Service
Azure Cognitive Services
Azure Cognitive Search
AI D
ep
th
AI Customization
The Modern Analytics Platform Journey
Custom AI
Data science
and Deep AI capability
Azure Databricks
Azure AI Infrastructure
Azure ML
Open Frameworks
Azure Cognitive Services
Azure Cognitive Search
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Azure Data Estate andArtificial Intelligence
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Artificial Intelligence Services
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AI Services
Cognitive ServicesAdd smart API capabilities to enable contextual interactions
Azure Bot ServiceIntelligent, serverless bot service that scales on demand
Azure DatabricksFast, easy, and collaborative Apache Spark-based analytics platform
Azure Bot ServiceBuild, train, and deploy models from the cloud to the edge
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Open Data Initiative
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Open Data Initiative - ODI
https://www.microsoft.com/en-us/open-data-initiative
Adobe, Microsoft, and SAP are partnering on theOpen Data Initiative to enable data to beexchanged—and enriched—across systems,making it a renewable resource that flows intointelligent applications.
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Microsoft Power Platform
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Microsoft Power platformOne connected platform that empowers everyone to innovate
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Dynamics 365
Office 365
Standalone Apps
MicrosoftPower Platform
Azure
Common Data Service for Apps
Data Connectors
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Power BI REST APIsPower BI Desktop
Prepare Explore ShareReport
Data sourcesSaaS solutionse.g. Marketo, Salesforce, GitHub, Google analytics
On-premises datae.g. Analysis Services
Organizational content packsCorporate data sources or external data services
Azure servicesAzure SQL, Stream Analytics…
Excel filesWorkbook data / data models
Power BI Desktop filesData from files, databases, Azure, and other sources
Power BI service
Data refresh
Visualizations
Live dashboards
Content packs Sharing & collaborationNatural language query
Reports
Datasets0100110101
Power BI
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Common Data Model - CDMWhat is the Common Data Model? – Meta Data SystemThe Common Data Model (CDM) is the shared data languageused by business and analytical applications. It consists of a setof a standardized, extensible data schemas published byMicrosoft and partners that enables consistency of data and itsmeaning across applications and business processes.
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Common Data Model – CDM in Action
• CDS for Apps : which supports Dynamics and PowerApps
• Industries such as healthcare are working closely with Microsoft to extend the CDM to their specific business concepts such as Patient, Care Plan through Industry Accelerators
• Power BI Dataflows allows you to ingest data into the CDM from a variety of sources such as Dynamics 365, Salesforce, Azure SQL Database, Excel or SharePoint.
• Azure Data Lake Storage Gen2(preview) – CDM brings semantic consistency to data with in the lake so that applications and services can interoperate more easily when data is in the same format
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Common Data Model - CDM
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Common Data Model Accelerator
• Extension to the Common Data Model to include concepts for the Electrical distributor industry
• System views that provide easy access to entities such as Products, Customers, Projects, BIM
• Sample app to show possibilities of the unified interface
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Common Data Service for Apps- CDS
Today, the CDM is used within Common Data Service (CDS) for Apps, which supports Dynamics 365, PowerApps, and the data-preparation capabilities in Power BI dataflows to create schematized files in Azure Data Lake. The CDM definitions are open and available to any service or application that wants to use them.