Data as a Profit Driver – Emerging Techniques to Monetize Data as a Strategic Asset

Data as a Profit Driver – Emerging Techniques
to Monetize Data as a Strategic Asset
Donna Burbank, Managing Director
Global Data Strategy, Ltd.
July 26th, 2018
Follow on Twitter @donnaburbank
Twitter Event hashtag: #DAStrategies

Global Data Strategy, Ltd. 2018
Donna Burbank
Donna is a recognised industry expert in
information management with over 20 years
of experience in data strategy, information
management, data modeling, metadata
management, and enterprise architecture.
Her background is multi-faceted across
consulting, product development, product
management, brand strategy, marketing,
and business leadership.
She is currently the Managing Director at
Global Data Strategy, Ltd., an international
information management consulting
company that specializes in the alignment of
business drivers with data-centric
technology. In past roles, she has served in
key brand strategy and product
management roles at CA Technologies and
Embarcadero Technologies for several of the
leading data management products in the
market.
As an active contributor to the data
management community, she is a long time
DAMA International member, Past President
and Advisor to the DAMA Rocky Mountain
chapter, and was recently awarded the
Excellence in Data Management Award from
DAMA International in 2016.
Donna is also an analyst at the Boulder BI
Train Trust (BBBT) where she provides advice
and gains insight on the latest BI and
Analytics software in the market. She was on
several review committees for the Object
Management Group’s for key information
management and process modeling
notations.
She has worked with dozens of Fortune 500
companies worldwide in the Americas,
Europe, Asia, and Africa and speaks regularly
at industry conferences. She has co-
authored two books: Data Modeling for the
Business and Data Modeling Made Simple
with ERwin Data Modeler and is a regular
contributor to industry publications. She can
be reached at
donna.burbank@globaldatastrategy.com
Donna is based in Boulder, Colorado, USA.
2
Follow on Twitter @donnaburbank
Twitter Event hashtag: #DAStrategies

DATAVERSITY Data Architecture Strategies
• January - on demand Panel: Emerging Trends in Data Architecture – What’s the Next Big Thing?
• February - on demand Building an Enterprise Data Strategy – Where to Start?
• March - on demand Modern Metadata Strategies
• April - on demand The Rise of the Graph Database
• May - on demand Data Architecture Best Practices for Today’s Rapidly Changing Data Landscape
• June - on demand Artificial Intelligence: Real-World Applications for Your Organization
• July Data as a Profit Driver – Emerging Techniques to Monetize Data as a Strategic Asset
• August Data Lake Architecture – Modern Strategies & Approaches
• Sept Master Data Management: Practical Strategies for Integrating into Your Data Architecture
• October Business-Centric Data Modeling: Strategies for Maximizing Business Benefit
• December Panel: Self-Service Reporting and Data Prep – Benefits & Risks
3
This Year’s Line Up for 2018

Today’s Topic
4
Data as a Profit Driver
• The Digital Economy is changing the way organizations do business across the globe, and is set
to transform the economy on an unprecedented scale.
• Business optimization, and entirely new business models are emerging as data-driven
technology provides unprecedented opportunity for innovation and change.
• In many organizations, data not only supports business profitability, but data itself has become
the critical business asset.
• What does it mean to leverage data as a business asset? And how can today’s data-centric
technologies support the data-driven revolution?

What is Data Monetization?
5
Data Monetization refers to using data for quantifiable economic benefit. This can
include indirect methods such as:
• measurable business performance improvements
• beneficial terms or conditions from business partners
• information bartering, productizing information (i.e., new information-based offerings)
• “informationalizing” products (i.e., including information as a value-add component of
an existing offering)
• or selling data outright (via a data broker or independently).
- Gartner IT Glossary

Data Monetization
Improvements to Core
Business
There are several ways to optimize growth through data
New Business ModelsNew Products and Services
• Optimize Revenue
• Improved marketing campaigns
• Customer Segmentation
• Pricing Optimization
• Etc.
• Minimize Costs
• Staff & Operational Efficiency
• Supply Chain Optimization
• Reduce Risk
• Regulatory Compliance
• Audit & Litigation Risk
• Smart City Initiatives: IoT
Monetization, Footfall Analytics, etc.
• Peer to Peer Ride Sharing: e.g. Uber,
Lyft, etc. are all based on data
• Social Networking Sites: Facebook,
Linkedin, etc. are all based on data
relationships.
• …and more
• Embedded Analytics Products: Selling
analytical tools key customer for
industry benchmarking, etc.
• Smart Metering: Allowing customers to
optimize their own energy usage
through value-added services.
• Revenue from Data Sets: Who may
have use for your data for other
purposes? Weather, transportation, etc.
• …and more….

Improvements to Core Business
• It is critical to continually show the value of any data-centric initiative.
• We often get so tied up in the project itself, we forget to show (& market) the value.
• For any data project, think of how you are improving the business in several key areas:
• Minimizing Costs
• Optimizing Revenue
• Reducing Risk
8
Making the Business Case
Part of your job is Marketing!
• Consider your audience (e.g. management).
• Which of these factors is most important to them?

• Minimizing Costs – this is often the easiest to show
• Reduction in Wasted Labor Costs: How much human capital is wasted due to poor data quality, lack of data
access, redundant data efforts, etc.?
• E.g. Mary spends 10 hours per week cleaning data before each marketing campaign.
• Calculate Mary’s hourly rate x # hours per week x # weeks -> $50/hr x 10 x 46 = $23,000 per year
• Improving Inefficient Business Processes: Can Supply Chain be made more efficient with a standardized set
of material master data?
• E.g. Efficiency gains of 2% can be achieved resulting in $X of savings.
• Cost Avoidance: Would improving address data quality reduce the number of returned mailings?
• E.g. Cost of each mailing x # returned x # times per year. -> $1 per mailing x 500 returned per week x
50 weeks of mailing = $25,000 per year
9
Minimizing Costs
Minimizing Costs

• Optimizing Revenue – How can better data improve business efficiency and profitability?
• Reduction in Costs or Inefficiencies: In some cases the benefits are simply the removal of the costs and inefficiencies from the
previous slide.
• Improved Business Performance: But more interesting is the ways data can be used to improve business effectiveness:
• Marketing Campaigns: Improved contact data (email, address, etc.) can improve marketing, but what new data sources can be
used? Social Media? Weather Data? Other?
• Advanced Analytics: How can analytics be used to improve the business, e.g. Price Optimization, Customer Segmentation, etc.
• New Data-Driven Applications: How can data and new data-driven technologies (e.g. AI) be used to improve the business, e.g.)
• Chat Bots: To streamline customer service
• Recommendation Engines: To enhance the sales cycle.
• New Revenue Streams: Can data be used for new revenue streams, e.g.
• Grant Funding: Data-driven analysis is often a key aspect of grant writing.
• Leveraging IP: Is there data that your company owns that can be monetized for research, marketing, etc.?
10
Optimizing Revenue
Optimizing Revenue

• Reducing Risk – Risk avoidance is a key aspect of any business. How can data and governance be used to minimize risk?
• Regulation: Industry regulations drive many data governance efforts including GDPR, HIPAA, BCBS 239, Spice, HIPAA, etc, etc.
• Product Traceability: Many food producers offer data-driven lineage showing the source of their food materials (e.g. fish catch).
• Health and Safety: Ensuring the health and safety of both customers and employees is critical.
• Employee: Data driven applications can help monitor employee health and safety activities (e.g. speeding).
• Customer: Is nutritional or allergen information correctly shown on menus? Does this information link to the actual food
source in the supply chain?
• Audit & Fines: Which industry regulations result in audit or fines? Has the organization been fined in the past? Can this be
quantified?
• Litigation: Has litigation occurred in the past due to data errors? What were the monetary sums?
11
Reducing Risk
Reducing Risk

Improvements to Core Business
• It’s often beneficial to turn your “back of the
envelope” calculations into a formal financial
projection.
• Benefits
• One time: e.g. sale of a data set, research
grant, etc.
• Recurring: e.g. staff productivity, ongoing
revenue, reduction in ongoing costs, etc.
• Costs:
• One time: e.g. software or hardware
purchase, initial training costs, etc.
• Recurring: e.g. Software subscription or
maintenance, staff salary, etc.
• Consider Capital Expenditure (Capex) vs.
Operational Expenditure (Opex)
• E.g. Cloud subscriptions can generally be
considered Opex.
• Speak with Finance to see what is beneficial
to them – they often have unique priorities
per industry.
12
Part of your job is Finance!

Calculate a Realistic “Break Even” Point
• Often, there is a period of “ramp up”
time where initial costs are greater than
the overall benefits.
• Software costs
• Training or Consulting Costs
• Initial loss of productivity as:
• Business processes are optimized
• Technical teams get up to speed
• It’s helpful to calculate a “break even”
point where the initiative begins to show
value.
13
Net-positive benefits may not happen immediately
Net positive value
Initial costs “Break even” point

Measuring Data Improvements
• Data Quality KPIs & Measures can aligned with concrete business drivers
• Helps prioritize efforts
• Basis for showing benefits and results
• For example, if we ensure that email address are 100% complete and 90% accurate, our marketing campaign
effectiveness can increase by 20%.
14
Aligning Data Quality Metrics with Business Improvements
KPI Current Target Status Business Benefits Type
Number of duplicate
customer records
2,000,000 1,000 • Correct # of customers for sales estimations
• Better single view of customer for integrated social
media campaign
• Reduce cost of physical mailing by $20K
• Cost savings
• Brand Reputation
• Marketing Innovation
Incorrect Salutation (Mr,
Ms, etc.)
5,000 1,000 •Customer satisfaction & Brand reputation harmed by
incorrect salutation.
•Targeted marketing campaigns by gender.
• Brand Reputation
• Campaign Effectiveness
Incorrect address/location 10,000 500 • Lower return rate on physical mailings
• Better targeted marketing by region.
• Cost Savings
• Campaign Effectiveness
Missing Sales Rep Assigned 500 100 • Ability for Sales to execute on customer leads
• Revenue growth
• Sales Effectiveness
Etc.
Business Driver: Improving Customer Data for Marketing Launch Campaign

Over $800M from Data Quality Improvement
15
• BT Group plc - a British multinational telecommunications
holding company which had the following challenges:
• Business Agility to deliver new products and services
• Regulatory Compliance to meet industry demands in a
heavily-regulated industry
• Customer Satisfaction through positive customer
interaction.
• Unfortunately, these efforts were being hampered by poor
data quality:
• Poor Supplier & Customer data hampered self-service
interactions
• Inaccurate inventory led to increased capital
expenditure
• Billing errors caused customer dissatisfaction
• To improve Data Quality, BT embarked on an enterprise-wide
data improvement journey which included both technology
and culture change.
The Challenge
• As a result, BT achieved in aggregate more than $800
million in quantified benefits including:
• Capital Cost Avoidance: Through improving accuracy of
inventory data, BT optimized equipment inventory and
reduced inventory costs.
• Improved Revenue Assurance: By improving Billing Data
accuracy, revenue loss decreased from more than 15% to
less than 1%.
• Productivity Gains in B2B Processes: By resolving data
quality issues, BT was able to automate customer and
supplier interactions, and reduce cycle times and manual
effort.
The Result
A Focus on Data Quality Yields Big Benefits for BT 1
1 Gartner, Publication Number G00138085, 24 March 2006

New Products & Services
• There are a large number of ways that new products and services can be created based on data.
The options will be unique to your company, but some examples include:
• Embedded Analytics Products: Selling analytical tools key customer for industry benchmarking, etc.
• Customer usage patterns: For large customers, showing purchasing across sites to help optimize their
business. Comparing with industry benchmarks, etc.
• Smart Metering: Allowing customers to optimize their own energy usage through value-added services.
• Revenue from Data Sets: Who may have use for your data for other purposes? Weather, transportation,
etc.
• A meteorology company selling weather data to retailers, engineering companies, etc
• Nonprofit selling anonymized demographic data to universities for research
• A shipping company has road geolocation data for rural areas – sold to manufacturing and delivery
companies in similar regions.
• Etc. – what data do you have that could be interesting/profitable to others?
17
Using Data for Strategic Advantage

Data-Driven Success: UK Consumer Energy Company
• While this UK-based consumer energy has been a leader in
consumer energy for over 100 years, it knew it had to
implement data-driven digital transformation in order to
remain a market leader:
• Decreasing product usage prompted need to diversify
capabilities
• Digital-savvy consumers demanding a new way of
interacting
• Issues with efficiency in core capabilities such as billing
and customer support due to data quality issues.
• To support both current and future business models, the
organization implemented a Data Strategy initiative:
• Data Architecture to identify critical data elements
• Data Governance to orchestrate data efforts
• Data Quality to cleanse and enrich core customer data.
• Data Platform Scalability to support traditional and new
data sources (e.g. IoT)
The Challenge
• Strengthening of Traditional Business Model: Better
quality customer data improved:
• Customer Billing & Payment
• Technical Support Efficiency
• Customer Satisfaction
• Transformation to New Digital Business Models: New
Consumer Business Models through
• Smart Metering
• Smart Home Products
• New Consumer Services for Energy Management
• Voice-activated Account Management
The Result
Transition to a Data-driven Digital Organization

International Telecom Company
• An international telecom company was looking to leverage data as a corporate asset.
• Data is seen as their most strategic asset and corporate focus
• Telecommunications is a secondary goal – becoming a commodity
• While data was used to improve their core business
• New Product & Service Development: Data is Anonymized & sent to digital arm for new product and
development. Data-driven prototyping – using analytics to see what products are working best and used most
• Operational Performance & Maintenance: Network Optimization, Integrating call failure information and
location information with survey data.
• Etc.
• The larger opportunity was new data monetization opportunities, e.g.
• Geospatial data and Footfall Analytics: Resell/leverage anonymized data for:
• Retail: how are consumers navigating store layouts?
• City Planners: What are pedestrian traffic patterns at rush hour?
• Internally: How are employees travelling between buildings?
Do we need a new lunch room?
Business Transformation to “Becoming a Data Company”

New Business Models
• Perhaps the most exciting monetization opportunities are completely new ways of doing business
that are now possible using data or unique combinations of data.
• Smart City Initiatives:
• IoT – e.g. Smart Parking systems – find available parking via your smart phone
• Footfall Analytics – understand pedestrian traffic patterns.
• Peer to Peer Ride Sharing: e.g. Uber, Lyft, etc. are all based on data
• Social Networking Sites: Facebook, Linkedin, etc. are all based on data relationships.
• Smart Buildings: Embedded sensors help detect materials failure.
• Smart Farming: IoT, connected devices, etc.
• …and more
21
New ways of doing business as a result of data

New Business Models
• Ridesharing companies like Uber and Lyft were able to disrupt the traditional taxi industry
through creative integration and usage of data.
22
Peer to Peer Ride Sharing – disrupting the transportation industry
GPS Data – tracking
drivers and riders
Airline arrival data– to predict
user volume & set pricing.
Algorithms – Setting pricing,
matching drivers, etc.
User Rating System –
Crowdsourced feedback loop.
Etc…– and more... Data is
their business…

Today’s Business Environment is Ripe for the
Business-Savvy Data Professional
• In the current environment of data-driven business, Data Professionals have an
opportunity to have a “seat at the table”
• Finding new opportunities to leverage data for business benefit
• Creating efficiencies & business process optimization
• Integrating data from disparate sources for new business insights
• Supporting organizational change
23

Summary
• The Data-Driven Digital Economy is changing the way organizations do business across
the globe. To stay competitive, strategic use of a data is a must.
• Significant gains can be made in improving core business through:
• Reducing costs
• Increasing revenue
• Minimizing Risks
• New products and services can augment core business operations with new revenue
streams.
• Innovative new business models can be realized by leveraging data. It’s no surprise
that some of the most successful companies in the world today are driven by data.

About Global Data Strategy, Ltd.
• Global Data Strategy is an international information management consulting company that specializes
in the alignment of business drivers with data-centric technology.
• Our passion is data, and helping organizations enrich their business opportunities through data and
information.
• Our core values center around providing solutions that are:
• Business-Driven: We put the needs of your business first, before we look at any technological solution.
• Clear & Relevant: We provide clear explanations using real-world examples, not technical jargon.
• Customized & Right-Sized: Our implementations are based on the unique needs of your organization’s
size, corporate culture, and geography.
• High Quality & Technically Precise: We pride ourselves in excellence of execution, and we attract high-
quality professionals with years of technical expertise in the industry.
25
Data-Driven Business Transformation
Business Strategy
Aligned With
Data Strategy
www.globaldatastrategy.com

DATAVERSITY Data Architecture Strategies
• January - on demand Panel: Emerging Trends in Data Architecture – What’s the Next Big Thing?
• February - on demand Building an Enterprise Data Strategy – Where to Start?
• March - on demand Modern Metadata Strategies
• April - on demand The Rise of the Graph Database: Practical Use Cases & Approaches to Benefit your Business
• May - on demand Data Architecture Best Practices for Today’s Rapidly Changing Data Landscape
• June –on demand Artificial Intelligence: Real-World Applications for Your Organization
• July – soon on demand Data as a Profit Driver – Emerging Techniques to Monetize Data as a Strategic Asset
• August Data Lake Architecture – Modern Strategies & Approaches
• Sept Master Data Management: Practical Strategies for Integrating into Your Data Architecture
• October Business-Centric Data Modeling: Strategies for Maximizing Business Benefit
• December Panel: Self-Service Reporting and Data Prep – Benefits & Risks
26
This Year’s Line Up for 2018 – Join Us Next Month

Questions?
27
Thoughts? Ideas?

Data as a Profit Driver – Emerging Techniques to Monetize Data as a Strategic Asset

Recomendados

Recomendados

Mais conteúdo relacionado

Mais procurados

Mais procurados (20)

Semelhante a Data as a Profit Driver – Emerging Techniques to Monetize Data as a Strategic Asset

Semelhante a Data as a Profit Driver – Emerging Techniques to Monetize Data as a Strategic Asset (20)

Mais de DATAVERSITY

Mais de DATAVERSITY (20)

Último

Último (20)

Data as a Profit Driver – Emerging Techniques to Monetize Data as a Strategic Asset