Community Chair

Digital Trinity and You

Change is one aspect which everyone is noticing, experiencing, feeling and fearing. It cannot be anticipated or predicted before a reasonable time. Data plays a huge role amidst this change and controlling its modulations. In this session, Christopher Surdak ( President, Surdak and company, deals with the notion of digital transformation and the impact it has on credit unions. He draws various insights in his discussion from his books, Data Crush and Jerk.

Six challenges of the New normal :

Six things in the world that are driving the way we live, the way we work, and which drive our expectations.

Quality: Consumers expect perfection. Deliver less, and your customers will abandon you forever. What matters is what a credit union does in the face of a problem, when it has only a limited duration of time to make it up to the consumer.

  1. Ubiquity: Globalization means anything, anywhere, anytime. Anything less is unacceptable.
  2. Immediacy: Immediate gratification. Instant and predictive services and solutions. Meeting expectations immediately or your customers lose interest.
  3. Disengagement: Don’t build, don’t run, don’t outsource, don’t care. The consumer only buys the result.  He has the attitude of “I don’t care what it takes for you to deliver a particular service to me. I want it. And within 30 seconds or less.”
  4. Intimacy: Customers hunger from other forms of connectedness. Feeling like a part, the community will be even more important as our needs are met more anonymously.
  5. Purpose: Credit unions should be able to support the customer’s need for and sense of purpose.

He discusses how these challenges lead to creepy expectations. Creepy expectations are expectations which initially arise from the need of intimacy, but gradually cross the line of being normal. Good Companies and analysts like Amazon look out for this creepiness edge.  The requirements of intimacy include anticipation needs, reverse grouping, E-coupons, and suggestion lists. The Creepy list includes geo-tracking, cookies, i-coupons, behavior modeling, and behavior manipulation. A good company is one which walks the edge between these two extremes. Example- Predictive shipping

By referring to his work in the second book, Jerk, he discusses that Cooperation is a survival strategy. We collaborate because together we can create better results than individually. The challenge with this is that cooperation requires submission.

The notion of social change is the currency of power. For social contracts to work, there must be a transfer of power, one to another; submission is exchanged for survival. In the contract Basis, distribution, application, and control of power is determined.

The Tool Trinity

For the longest of time, the basis of power has been knowledge, the distribution is memory, the application is storytelling and control is teaching.

The Dirt Trinity

From the tool trinity, we shifted to the dirt trinity, wherein the basis of power was land, whose distribution was through heredity, the application is through Edict, and control is violence.

The Analog Trinity

This originated 250  years ago wherein the basis of power was capital, whose distribution was in the form of bureaucracy, was applied through the process, and controlled through rules.

The Digital Trinity

This is the new realm we are now moving towards. In the digital trinity, the basis of power is information, it is distributed through mobility, applied through social media which creates social media based wealth, and is controlled through data analytics.

The shift from analog to digital trinity is the digital transformation. According to Christopher,  this is not technological change. Technology enables this change, but it is majorly a social and economic development.

Digital Transformation

It is enhancing the outcome of business operations through the effective use of information. It is more about innovation rather than improvement. He states that digital transformation is the reason that 51% of the companies in Fortune 500 list of 2000, fell off the list by 2015.

Currently, 1/5th of the global economy exists in countries whose central banks have a negative interest rate.

Christopher’s book, "Jerk" means an increasing rate of acceleration, an instantaneous change of force, which is highly destructive to systems which are not designed for it. Companies like Uber and Airbnb have created a massive disruption in the economy by creating new ways to deliver customer value. By merely using data and analytics through their business models, they can jerk their entire economy. Here are the reasons which are discussed by him.

The “Dirty Dozen” of being a Jerk. How jerks do what they do.

  1. Jerks use other people’s capital. Example- Uber, Airbnb
  2. Jerks replace capital with information. Jerks do not monetize data; they data-fi money. They generate information wealth. Example- Facebook.
  3. Jerks monetize context, not content. Example- Uber is a context engine.
  4. Jerks eliminate friction. Capitals in motion have no value. Information has no value at rest.
  5. Jerks replace value chains with value webs.
  6. Jerks invert economies of scale and scope.
  7. Jerks sell with and through, not to. Example: Friend and family suggestions in Amazon
  8. Jerks print their own money. Example- Loyalty points.
  9. Jerks flout the rules. They are led by analytics.
  10. Jerks hightail it. They try to make their products and services as efficient as possible. They use analytics to determine the unserved hightail and low tail which is missed through analog averageness.
  11. Jerks do, then learn. Not learn and do. A data analyst should be first able to see and experience the impact rather than waiting for research.
  12. Jerks look forward not backward. Analogs believe in reports  Data should be used to make better predictions of the future.

Credit unions can gain massive insights from these principles. For example - Loyalty reward system is a solution for focusing on context rather than content. Predictive suggestions and selling through personal interactions and relationships is an example of selling with and through, and not to. They can use these principles by adopting them in their daily functions.

Action should be at the speed of insight. What can be done about Jerks?

  1. Use your capital to DIE: Discover, Infiltrate, and Exploit. If you have capital in your business, you should use it to innovate not within the box, but you should be able to switch boxes and innovate.
  2. Rewrite your books: If you do not value speed and time, if your ROI analysis does not cover the changing context, you will not be able to prepare for it.  You can change your organization only through metrics and rewards. It is important to hire the right people.
  3. Regulatory and legal backlash. For example - Fanduel not only did they stick to elective compliance but also gained legislation by plebiscite.
  4. Annihilate your process: Focus on innovation rather than improvement. Christopher quotes his book Data Crush, and suggests to  “ Cut every cycle time in half, every 12 months.”
  5. Fail fast: Fail small and fail fast. This leads to practical analysis and innovation.
  6. Seek discomfort: Digital transformation should scare you, and you should be able to embrace the changes.
  7. Analogs can go digital: They can service hightail, go through gamification, diseconomies of scale and scope, put customers to work, owing to intimacy and purpose, do, then learn attitude and fail fast approach.

An interesting question that Christopher discusses towards the end of this session is whether loans are products or experiences?

The approach used by First Tech credit union of “life stage” strategy is a right approach.         

But Christoph highlights that not all lives are lived the same. Boomers and Gen-X are object-oriented, and millennials and Gen Z are experience oriented. This highlights the importance of context.

In credit unions, there is an increasing requirement to solve customer’s needs for intimacy and purpose in the face of digital transformation and its disruption.

WATCH FULL PANEL SESSION HERE

E-mail me when people leave their comments –

You need to be a member of CULytics Community to add comments!

Join CULytics Community

 

advantedge
altair
ibi
arka
trellance
coopfs
dfa
wherescape
alkami
prismacampaigns
marquis
aiq
totex
cnet
datava
aun
cinch
know

Related Post

 

Ad Unit Settings






Ad Url Settings

 

api-lead-approach
the-amazon-lending-experience
executing-advanced-analytics-do-s-and-don-t
lending-transformation-old-vs-new
data-journey-building-strong-analytical-practices
4-step-iterative-process-building-a-relevant-analytics-practice
significant-measures-towards-new-normal
building-a-strong-analytics-practice-recipe-for-success
data-warehouse-evaluation-and-implementation
explainable-ai-trust-and-transparency
forecasting
top-50-members-using-transactional-website-jun-2020
top-50-cus-with-highest-and-lowest-efficiency-june-2020
importance-of-financial-risk-management
secret-sauce-for-long-term-sustainable-business-intelligence-succ
top-pfm-technologies
secret-sauce-for-long-term-sustainable-business-intelligence-succ
top-pfm-technologies
data-warehouse-and-bi-technologies-opportunities-challenges
top-chatbot-technologies
keys-to-building-an-effective-branch-or-atm-network
top-50-credit-unions-with-highest-and-lowest-accounts-per-member
lowest-and-highest-net-income-per-branch
marketing-holy-grail
top-50-most-and-least-delinquent-credit-unions
modern-marketing-technologies
incremental-low-cost-data-driven-wins
power-of-storytelling
the-cost-of-not-investing-in-data-governance
questions-you-should-ask-before-investing-in-data-warehouse
learnings-from-new-data-based-on-auto-loan-pricing
5-questions-you-need-to-ask-before-investing-in-data-governance
digital-marketing-maturity-models-for-credit-unions
marketing-expense-per-member
top-2-reasons-that-are-holding-credit-unions-back-when-they-are-i
using-data-analytics-to-manage-lending-complexity-while-driving-h
5-reasons-your-credit-union-should-invest-in-data-and-digital-now
top-50-most-and-least-efficient-credit-unions
retail-financial-services-outlook-during-covid-19
use-of-operational-analytics-to-mitigate-the-impact-of-covid-19
top-50-credit-unions-based-on-asset-size
cu-peer-comparison-dashboard
cu-peer-benchmark
all-about-machine-learning-engineering
top-web-design-trends
most-important-social-media-marketing-trends
state-of-digital-marketing-maturing-in-credit-unions
top-kpis-for-email-marketing
data-cloud-and-the-digital-transformation-imperative
digital-trinity-and-you
phases-of-financial-industry
analytics-roundtable-workshop
invitation-to-join-digital-transformation-hub
analytics-in-the-credit-union-business
value-of-member-centricity-and-analytics-in-the-growth-of-cus
all-about-membership-analytics
top-fraud-management-technologies
getting-started-with-your-data-analytics-journey
explore-vizualization-for-credit-unions
investment-in-website-personalization-technologies
data-analytics-supporting-cu-s-first-member-philosophy
loyalty-rewards-and-retention-technologies
member-experience-analytics
channel-analytics-and-its-importance
project-portfolio-management-technologies
investment-in-self-service-data-preparation-technologies
self-service-data-preparation-technologies
new-frontier-in-customer-experience-management
role-of-marketing-analytics-in-credit-unions
important-aspects-of-consumer-lending-analytics
kpis-on-website-analytics
journey-towards-bank-less-banking
investment-in-crm-technologies
top-omni-channel-vendors
conversational-banking-solutions
/top-kpis-for-chief-information-officer
mistakes-to-avoid-when-implementing-a-omnichannel-member
top-things-to-consider-when-building-dashboards
making-digital-marketing-more-agile-through-tag-managers
cecl-solution-providers
mistakes-to-avoid-while-implementing-marketing-automation
p2p-payment-integrated-solutions
kpis-for-social-media-tracking
kpis-for-human-resources-management
investment-in-fintechs-should-or-should-not
top-kpis-for-online-banking
investment-in-marketing-automation-technologies
investment-in-e-signature-technologies-should-or-should-not
tips-and-tricks-to-a-successful-bi-program
kpis-for-credit-card-business
kpis-for-digital-marketing
kpis-for-consumer-lending
hot-topics-for-credit-union-data-leaders
kpis-for-debt-collections
kpis-for-finance
website-personalization-tools
data-integration-technologies
robotic-process-automation-tools
why-data-analytics-initiatives-fail
electronic-signature-softwares
data-governance-tools-for-credit-unions
digital-and-mobile-banking-technologies
report-inconsistencies-are-frustrating
is-your-culture-ready-for-data-analytics
three-big-data-myths
turning-transaction-data-into-a-goldmine-a-becu-case-study
call-for-presentation-for-2019-credit-union-analytics-summit-is-n
top-10-keys-to-successful-data-analytics-practice
credit-union-chooses-accountscore-for-open-banking-transaction-da
how-much-do-you-spend-to-serve-a-customer
marketing-automation-technologies-for-credit-union
alexa-ask-first-abilene-fcu-for-my-balance
dataweb-content-management-technologies-for-credit-unions
efficiency-ratio
web-analytics-technologies
data-warehousing-software-for-banks
customer-experience-software
the-best-kept-secret-for-credit-union-data-analytics
mark-sievewright-on-technology-trends
naveen-jain-on-credit-union-analytics-summit-2018
why-analytics-doesn-t-make-a-difference-by-gary-angel
cuas2018-harnessing-the-right-data
build-a-financial-phone-assistant-for-your-credit-union-in-3-step
2018-culytics-analytics-challenge-winner
update-from-naveen
error-resolution
benefits-of-conversational-apps
who-are-your-most-valuable-members-part-1
how-alexa-can-help-your-credit-union
top-10-kpis-for-measuring-retail-channel-performance
how-much-is-too-much-personalization
top-10-kpis-for-measuring-contact-center-efficiency
pressure-on-margins-for-auto-loans-indirect-auto-loans-declining
best-business-intelligence-technologies-for-credit-unions
establishing-a-thriving-data-analytics-practice-is-a-journey
educational-presentations-from-the-2017-axfi-conference
modelling-alternatives-for-cecl-a-deep-future-analytics-study
data-analytics-use-cases-for-credit-unions-infographic
data-analytics-opportunities-in-credit-union-business
loan-application-analytics-with-cufx
machine-learning-delivers-great-consumer-experiences
deep-insights-of-credit-union-members-data-with-machine-learning
web-analytics-reporting-tips-for-credit-unions
big-data-strategy-roadmap-our-data-journey
webinar-framework-for-member-focused-decision-making
too-many-regulations-hurt-credit-union-members
digital-marketing-automation-solutions
online-banking-boom
transformation-transactions-to-relationships
top-dispute-management-technologies
2020-retail-trends
future-of-artificial-intelligence
2020-culytics-summit-attendee-dashboard
repositioning-the-role-of-marketing
marketing-automation-a-step-towards-marketing-transformation
strategic-agility
using-data-to-navigate-through-the-new-normal
digital-transformation-bcu
highest-and-lowest-new-loan-balances-per-branch-as-of-jun-2020
-new-members-ratio-as-of-june-2020
cus-with-highest-and-lowest-loan-grants-per-member-june-2020
self-service-data-preparation-technologies
highest-and-lowest-marketing-expense-per-member-june-2020
the-amazon-lending-experience
api-lead-approach
4-step-iterative-process-building-a-relevant-analytics-practice
data-journey-building-strong-analytical-practices
post-election-the-cu-outlook
most-and-least-delinquent-credit-unions-sept-2020
leveraging-ach-data-to-produce-real-outcomes
member-engagement-scores-benefits
member-engagement-key-to-serve-the-best
story-of-james-an-intelligence-transformation
executive-kpis-the-pulse-of-the-organization
untangling-member-journey
onboarding-strategy-to-deliver-success
the-importance-of-digital-technologies
top-interactive-financial-calculators
using-artificial-intelligence-to-improve-your-productivity
organizational-transformation-to-drive-growth
multi-year-journey-through-data-transformation
top-50-cus-with-the-highest-and-lowest-member-per-branch
digital-transformation-lessons-through-the-eyes-of-a-ceo
organizational-readiness-for-digital-transformation
ruthless-prioritization-to-do-more-to-learn-more-and-to-earn-more
performance-measures-for-digital-services
analytical-maturity-journey-towards-growth
less-is-more-the-necessity-of-focus-for-strategic-success
solving-the-crm-mrm-puzzle
insights-driven-messaging-member-and-product-onboarding
performance-measures-for-marketing
data-insights-that-drive-member-product-innovation
solving-the-crm-mrm-puzzle
the-agility-flywheel-a-strategy-that-never-goes-out-of-the-way
artificial-intelligence-as-a-playing-field-for-credit-unions
performance-measures-for-call-centers
top-automl-technologies
performance-measures-for-lending
building-business-case-for-data-analytics
driving-innovation-and-change
data-analyze-decide-and-create
digital-readiness-important-steps-to-achieve
digital-readiness-important-steps-to-achieve
enabling-credit-unions-with-ai
culytics-virtual-summit-2022-a-resounding-success
culytics-virtual-summit-2022-day-1
digital-banking-roundtable
digital-marketing-roundtable
transformative-lessons-from-a-chief-digital-officer
data-analytics-roundtable-mar-11
rewind-2022-culytics-day-key-highlights
data-analytics-team-roles
data-warehouse-development
data-analytics-team-size
is-your-data-analytics-program-not-delivering-results
active-deposit-management-for-profitable-growth
data-modeling
maximize-your-success-with-2023-CULytics-summit
biggest-opportunities-for-credit-unions
should-ceos-attend-the-culytics-summit
the-cost-of-a-wrong-decision
biggest-roadblocks-in-becoming-data-driven
a-journey-for-all-organizational-maturity-levels
maximize-your-data-analytics-checkup
navigating-the-data-analytics-landscape
improving-data-literacy
why-credit-union-leaders-should-invest-in-their-teams
why-credit-unions-should-not-invest-in-building-predictive-models
why-should-measure-the-success-of-data-analytics-program
cost-of-choosing-the-wrong-data-analytics-technology-stack
why-data-analytics-strategy-focus-on-supply-and-demand-side
kpis-to-measure-the-success-of-data-analytics-program
data-analytics-for-credit-union-branch-heads
data-organizing-principles
top-data-warehouse-storage-technologies
discover-the-hidden-truth-behind-watermelon-kpis
unveiling-the-hidden-dangers-of-cobra-effect-on-kpis
are-you-accurately-interpreting-your-kpi
unmasking-biases-a-guide-to-data-analysis-and-kpi-definition
uncover-the-power-of-proxy-kpis
unraveling-the-hidden-impact-of-sampling-bias-in-credit-unions
bi-department-structure
hidden-impact-of-confirmation-bias-in-credit-unions
getting-executive-attention-for-your-data-analytics-program
uncovering-biases-in-data-preprocessing
navigating-missing-data-in-credit-unions
navigating-sampling-bias-in-cu
unleash-the-power-of-real-time-data-use-cases
how-confirmation-bias-impacts-cus
breaking-down-selection-bias-in-credit-unions
unmasking-reporting-bias
elevate-your-cu-with-data-analytics-expertise
understanding-and-tackling-volunteer-bias-in-credit-unions
time-period-bias-in-credit-union
overcoming-biases-in-credit-unions
embracing-the-future-fast-future-fundamentals-program-equips-cred
unlock-growth-and-efficiency-credit-unions-guide-to-generative-ai
how-better-data-and-behavioral-biometrics-can-help-credit-unions-
harnessing-the-power-of-data-in-credit-unions
leveraging-third-party-data-a-strategic-guide-for-credit-unions
unlocking-member-insights-how-cus-can-leverage-third-party-data
enhancing-customer-experience-through-third-party-data
third-party-data-integration-techniques-and-technologies
the-future-of-lending-third-party-data-role-in-credit-decisioning
how-third-party-information-shapes-cu-strategies
using-data-to-improve-access-to-credit-for-low-income-members
designing-financial-products-for-low-income-members-using-data
measuring-and-enhancing-the-impact-of-support-programs
data-governance-why-selling-internally-is-important
selling-data-governance-in-your-credit-union
building-a-business-case-and-engaging-stakeholders
creating-a-data-governance-roadmap-and-executing-it
measuring-and-demonstrating-the-impact-of-data-governance
sustaining-momentum-keeping-data-governance-a-priority
overcoming-challenges-in-transaction-data-analysis-credit-unions
empowering-members-through-transaction-data
how-credit-unions-leverage-transaction-data-best-practices
unlocking-financial-independence-the-power-of-transaction-data
the-power-of-transaction-data-enrichment
avoid-financial-reputation-and-member-trust-issues
introduction-to-model-risk-management
week-1-mrm-a-practitioner-s-approach
week-2-guide-to-identifying-and-maintaining-models
survey-insights-navigating-mrm-in-credit-unions
week-3-application-of-mrm-insights-to-sound-model-development-eff
unlocking-the-secrets-to-attracting-gen-y-and-z
creating-a-seamless-member-experience-for-gen-y-and-gen-z
data-analytics-maturity-assessment-report
marketing-to-gen-y-and-z-strategies-that-work-for-credit-unions
the-imperative-of-engaging-millennials-and-gen-z
cu-build-lasting-relationships-with-gen-z-financial-literacy
how-social-responsibility-drives-gen-z-membership
loyalty-programs-that-work-keeping-gen-y-and-z-members-engaged
insights-on-engaging-millennials-and-gen-z-at-credit-union
ai-driven-member-experience
streamlining-operations-with-ai
innovation-and-member-inclusion-in-ai-credit-risk-models
ai-risk-management-enhancing-fraud-detection-and-cybersecurity
how-ai-is-transforming-data-analytics-for-credit-union
overcoming-ai-adoption-challenges-in-credit-unions
the-state-of-ai-in-credit-unions-survey-insights
creating-a-culture-of-innovation
building-the-foundation
closing-the-talent-gap