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Joint presentation with I&T's covering the proliferation of data available to insurance companies today and a high level view of searching for value and leveraging the relevant and useful buried in all of the trivia.
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The Proliferation of Data: Finding Meaning Amidst the Noise
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Big Data = Transactions + Interactions + Observations
The Proliferation of Data
Transactional– Informational – Behavioral - Environmental
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• Data availability and accumulation is accelerating in form and content
Ø Variety: not just text and faxq Images, blogs, telemetrics , social media, affiliation cards, etc.q Integration of all interactions into “Warehouses”
Ø Volume: there is a lot of it• More sources, more data, and the sources are like waterfalls vs trickles• Increased collection of internal transaction and contact information
Ø Velocity: rate of change is acceleratingq More sources, more data, more churningq Real-time sources like telemetrics and social media
• Two attributes of “Big Data” describe usefulness
Ø Veracity: When does “good enough” become “garbage”
Ø Value: Finally, the real question – what data is adding meaningful value
So this is “Big”?The Proliferation of Data
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Big Data Solutions Landscape Crowded and Diverse
The Proliferation of Data
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“Exaponential” Growth in Data
On the Internet, every 60 Seconds adds…Ø 168 million+ emails sentØ 1.2 million+ Facebook postsØ 690,000+ Google searches Ø 370,000+ minutes of calls on SkypeØ 98,000 tweets on TwitterØ 20,000 new posts on TumblerØ 13,000 IPhone apps downloaded
Source: go-globe.com
Ø 13,000+ hours Pandora music streamedØ 6,600+ pictures uploaded on FlickrØ 1,200+ new Craigslist adsØ 600+ videos are uploaded on YouTube Ø 100+ questions asked on Answers.comØ 100 accounts created on LinkedInØ 30 new domains are registered
One Exabyte = 10 to the 18th
ONE THOUSAND PETABYTESONE MILLION TERABYTESONE BILLION GIGABYTES
The Proliferation of Data
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The Proliferation of Data
Growth in Data is Personal…Private…Social
Privacy and security needs intensified by personal nature of data
Cyberinsurance huge marketData “ownership” untested
• Data Theft / Loss• Legacy Complications• Collection Complexity• Interpretation Issues• Error Exposures• Costs (Collect/Scrub)
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Social Media Landscape Crowded…Huge Data SourceThe Proliferation of Data
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Social Media a Double-Edged Sword
Key Issues• Understand if/when/how your customers & potential customers are using it• Messaging and themes should be integrated across media platforms• Customers and noncustomers are empowered to say what they want, it is a free-for-all• It takes qualified and dedicated staff and time to be effective• Senior executive sponsorship and full support is critical
Risks to be managed• Regulatory considerations – what you don’t know can hurt you• Uncontrolled risks – agents and employees, at work and at home, impact company• Power shift to Consumer – their voice is being heard whether or not you are listening
Operational Considerations• Exposure assessment: where are all the uses, agent practices, reputational damage• Competitive scan: what are the Best Practices, how are competitors positioned• Strategy development: which, where, when, and how much; staffing & process changes• Process integration: marketing, underwriting, claims, customer service• Implementation planning: steps, staffing, governance, metrics
Finding Meaning Amidst the Noise
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§ UBI opened door§ Health Information rapid source of growth§ New Markets like Wearables
§ Product Differentiation§ Pricing Accuracy§ Makes Sense, Controllable § Minimize Hard to Understand Factors (credit)
Exploring17%
Inactive23%
Implemented 60%
UBI sales expected to grow from $50M in 2011 to approximately $2.6B by 2015.
Telemetrics (like UBI) Another Huge Source of DataThe Proliferation of Data
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UBI is “Big Deal” – Implications?
Key Issues• Too many devices, not enough standards – which to pick and why? Vendor viability?• More and more data – how is it scrubbed and integrated into existing data? Supplemented?• Large and complex investment, works across silo’s and requires extensive collaboration• It takes qualified and dedicated staff and time to be effective• Legacy systems and redundant dirty data remain an issue
Risks to be managed• Regulatory considerations? Mandated restrictions that create complexity, data risks• What about privacy? Discoverability for nonrelated trials, consumer opinions over time§ Diminished risk pooling? As use grows, disparity between risk classes will grow§ Competitiveness? If more poor drivers, will non-UBI be able to pool risks to larger market
Operational Considerations§ System selection process: vendor evaluation and assessment require discipline§ Enterprise wide project management: PMO style oversight and coordination§ Introduction impacts processes in operations: redesign and optimization efforts to integrate
The Proliferation of Data
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Add Demographic Shifts
Five Generations of Consumers, Large New Wave Coming(% of Total Population)
Increasing Ethnic Diversity
The Digital Generations- powerful consumers
High Tech Low Tech
Finding Meaning Amidst the Noise
• Pricing Differentiation• Total Value• Risk Identification• Service Insights• Immediate Response• Retention / Loyalty• Market Sentiment• Fraud Detection
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Understand Changes in Service Expectations and Strategies
Company’s Areas of Focus
Increasing Customer Expectations• Immediacy / 24x7 access• Transparency• Personal service relationships• Language differences• Benchmarking performance within and outside the industry
Finding Meaning Amidst the Noise
Expanding Accessibility 100%
Accelerating Service Delivery 96%
Increasing Hours and Days of Service Availability 82%
Creating Different Levels of Customer Service 63%
Aligning Operations with Customer Markets 63%
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“Big Data” + Analytics = Customer Awareness
Getting to Information from Big Data Requires:• A “Value” filter has got to start being applied against volume and variety• “Veracity”, or quality, is going to have to improve: TMI + GIGO = FAIL• Data is meaningless without people who understand what it means (same with analytics)• This is going to be an area filled with lessons learned, probably more so than any other
The Personal Nature of the Data Brings New Risks• Regulatory issues – collection methods can become illegal overnight• Privacy issues and exposure risk are all dynamic unknowns• Sources can change their technologies, accessibility, fees, structure• Externally gained date from vendor controlled domains create dependencies• GIGO + TMI = FAIL
Operational Considerations – Key Factors in Getting Value from Big Data• Value analysis of what data contributes to the business• Governance and process design and monitoring• Quality control practices and measures• Typical implementation in an extremely high risk area• Bringing ability to ensure business understanding is incorporated into “Big Data” projects
Finding Meaning Amidst the Noise
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Leads to Evolving Service Delivery Model
One Size Fits All§ Same service for all segments
§ Over invest in some, under invest in others
§ One model to manage across lines and customers
§ Differentiation at company level based on brand or channel
§ Easier to match capabilities, one target to work with
Individualized Service§ Segmented customer needs and
economic value
§ Investment in service aligned with need/value tradeoff
§ Service differentiation varies by segment based on value
§ More models to manage, more challenging
§ Delivery is people based, harder to replicate
Finding Meaning Amidst the Noise
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Technology Initiatives Continue to Face Challenges
- 5 of top 6 challenges are people issues (availability, expertise)- The other one is budget, the place where people needs solved
$
Finding Meaning Amidst the Noise
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1. Best Practice Driven Transaction Processing Systems‒ Modular replacement if necessary; stepwise, wrap, LOB, or Bang‒ Integrated and adaptable business rules, distributable (n-tier)‒ Data adaptability, integrity/quality and accessibility
2. Multi-faceted AnalyticsØ Straddle pricing + marketing + underwriting + servicing + claims + external dataØ Integrated across functionsØ From workflow to predictive modeling, key to loss management
3. Empowered AccessibilityØ Customer and agents apps for self-service, data capture, personalizationØ Enterprise-wide standardized views and definitions
Operationalizing New Data and Tools Requires Solid FoundationFinding Meaning Amidst the Noise
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Execution Excellence Based on Three Guiding Principles
1. Have an executive sponsored roadmap that clearly outlines.§ What resources will be needed for how long, § Where, when, and how will analytics enhance process and awareness, § Which tools will be used, and § How will success be measured.
2. Use data that is comprehensive, accurate, and current. § Not necessarily 100%, some have used only 70%§ Must be representative.
3. Staff with talented and engaged people. § Completely understand business problem and are proficient with data. § Strength depends on team not individual – business and tool experts§ Inquisitive and constantly challenging assumptions and perceived “givens”
Finding Meaning Amidst the Noise
