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David Rogers (racing driver)

From Wikipedia, the free encyclopedia

David Rogers
Born(1955-04-19)April 19, 1955
Orlando, Florida
DiedMarch 8, 2020(2020-03-08) (aged 64)
Achievements1994 NASCAR Weekly Series national champion
NASCAR Xfinity Series career
5 races run over 3 years
Best finish66th (1982)
First race1982 Goody's 300 (Daytona)
Last race1992 Fram Filter 500K (Talladega)
Wins Top tens Poles
0 1 0

David Rogers (April 19, 1955 – March 8, 2020) was an American racing driver who won the NASCAR Weekly Racing Series national championship in 1994.[1]

YouTube Encyclopedic

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  • (9-10-16) Sportsman Heat Race In-Car with (#44) Dave Rodgers
  • NASCAR Media Center Interview Carl Edwards, Joe Gibbs, Dave Rogers at RIR - Let's Talk Racing
  • JG, Dave Rogers, Denny Hamlin CS Post Race Winners Interview

Transcription

Racing career

Rogers won hundreds of short-track races throughout Florida. He was crowned NASCAR’s National Short Track Champion in 1994 after, while driving his own late model, he won all 22 races at Volusia County Speedway in Barberville, Florida, making him the first NASCAR Weekly Series national champion to complete a season undefeated. He had wins in all of New Smyrna Speedway’s biggest races, including the Florida Governor’s Cup, Orange Blossom 100, Red Eye 100, Pete Orr Memorial and World Series of Asphalt Stock Car Racing.[1][2]

He competed in 5 NASCAR Busch Series events, 3 in 1982, 1 in 1983 and the other in 1992. His best finish was 9th at Charlotte Motor Speedway, he also failed to qualify to one Busch Series event. He ran 2 ARCA Racing Series races, failed to qualify to one and withdrew from other, between 1980 and 1984.

Rogers also ran 3 NASCAR Southeast Series races, between 1991 and 1992, with a best finish of 6th at Volusia County Speedway.

He used to compete annually in the Snowball Derby, his best finish was 6th (twice), in 2008 and 2013. His last race was in the 2019 Snowball Derby.

Motorsports career results

NASCAR

(key) (Bold – Pole position awarded by qualifying time. Italics – Pole position earned by points standings or practice time. * – Most laps led.)

Busch Series

NASCAR Busch Series results
Year Team No. Make 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 NBSC Pts Ref
1982 Rogers Racing 22 Pontiac DAY
14
RCH BRI MAR DAR HCY SBO CRW RCH LGY DOV HCY CLT
9
ASH HCY SBO CAR CRW SBO HCY LGY IRP BRI HCY RCH MAR 66th 383 [3]
23 CLT
13
HCY MAR
1983 92 DAY
34
RCH CAR HCY MAR NWS SBO GPS LGY DOV BRI CLT SBO HCY ROU SBO ROU CRW ROU SBO HCY LGY IRP GPS BRI HCY DAR RCH NWS SBO MAR ROU CLT HCY MAR 143rd 61 [4]
1992 Rogers Racing 58 Chevy DAY CAR RCH ATL MAR DAR BRI HCY LAN DUB NZH CLT DOV ROU MYB GLN VOL NHA TAL
23
IRP ROU MCH NHA BRI DAR RCH DOV CLT
DNQ
MAR CAR HCY 102nd 94 [5]

ARCA Permatex SuperCar Series

(key) (Bold – Pole position awarded by qualifying time. Italics – Pole position earned by points standings or practice time. * – Most laps led.)

ARCA Permatex SuperCar Series results
Year Team No. Make 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 APSCSC Pts Ref
1980 Rogers Racing 22 Pontiac DAY NWS FRS FRS MCH TAL
17
IMS FRS MCH NA - [6]
1981 02 DAY
DNQ
DSP FRS FRS BFS TAL FRS COR NA - [7]
1983 Finney Racing 80 Buick DAY NSV TAL LPR LPR ISF IRP SSP FRS BFS WIN LPR POC TAL
Wth
MCS FRS MIL DSF ZAN SND NA - [8]
1984 DAY
18
ATL TAL CSP SMS FRS MCS LCS IRP TAL FRS ISF DSF TOL MGR NA - [9]

References

  1. ^ a b Schaefer, Paul. Where Stars Are Born: Celebrating 25 Years of NASCAR Weekly Racing. Coastal 181, Newburyport, Massachusetts, 2006. ISBN 0-9789261-0-2. pp. 97-102.
  2. ^ Kelly, Godwin. "Short-track legend David Rogers dies". Daytona Beach News-Journal Online.
  3. ^ "David Rogers – 1982 NASCAR Budweiser Late Model Sportsman Series Results". Racing-Reference. NASCAR Digital Media, LLC. Retrieved March 10, 2021.
  4. ^ "David Rogers – 1983 NASCAR Budweiser Late Model Sportsman Series Results". Racing-Reference. NASCAR Digital Media, LLC. Retrieved March 10, 2021.
  5. ^ "David Rogers – 1992 NASCAR Busch Grand National Series Results". Racing-Reference. NASCAR Digital Media, LLC. Retrieved March 10, 2021.
  6. ^ "David Rogers – 1980 ARCA Permatex SuperCar Series Results". Racing-Reference. NASCAR Digital Media, LLC. Retrieved March 10, 2021.
  7. ^ "David Rogers – 1981 ARCA Permatex SuperCar Series Results". Racing-Reference. NASCAR Digital Media, LLC. Retrieved March 10, 2021.
  8. ^ "David Rogers – 1983 ARCA Permatex SuperCar Series Results". Racing-Reference. NASCAR Digital Media, LLC. Retrieved March 10, 2021.
  9. ^ "David Rogers – 1984 ARCA Permatex SuperCar Series Results". Racing-Reference. NASCAR Digital Media, LLC. Retrieved March 10, 2021.

External links

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2. Harness Customer Networks - Businesses must learn to see customers differently, as nodes in network - Firms are still the greatest engines for innovation but together with delivering value to customers and communicating with them they must also engage with their customer network - The Marketing Funnel allows to understand how customer networks have such great impact on business’ relationships to customers by mapping out the progression of a potential customer. Businesses need to go beyond driving potential customers to purchase (action) and repeat it (loyalty), but they need to engage, nurture - There are 5 core behaviors that drive customers in the digital experiences 1. Access: simplicity, ubiquity, flexibility, convenience  m-commerce, omni-channel, cloud, on-demand 2. Engage: think like a media company, focus on earning attention  product demos, storytelling, utility, brands as publishers 3. Customize: understand where customers’ needs and behaviors diverge  recommendation engines, personalized interfaces, products, messages 4. Connect: part of your customers’ conversations  social listening and customer service, ask for ideas, hosting a community 5. Collaborate: understand the motivations of your contributors  crowdfunding, open competition, collaborative platforms - The Customer Network Strategy Generator helps you develop new strategic ideas for engaging and creating value with networked customers 1. Objective setting 2. Customer selection and focusing 3. Strategy selection (between A, E, C, C, C): use objectives and target customers 4. Concept / Idea generation 5. Define impact: bring each idea to the objective - Mass Customization: personalized products at normal prices  Types of mass customization • Collaborative: dialogue to client to understand and meet the needs (NikeID) • Adaptive: one standard product with customization options (Adicolor by Adidas) • Cosmetic: same product but different advertising / packaging for different customers (Nutella jars) • Transparent: customized products without saying it (Amazon’s recommendations)  Driven by • Market demand (mass market is dead) • Market competition (great product variety, short product lifecycle) • Technological revolutions (flexibility manufacturing, adaptation)  How to achieve mass customization • Modularization: units designed independently that function as a whole • Servitization: from selling product to selling product service systems

3. Build Platforms, Not Just Products - The new emerging trend of our economy is the platform - The digital revolution is shifting the role of competition, increasing the role of coopetition:  More transparent value chains  Convergence of traditional industries  New ecosystems (AMZ) - Process: 1. Digitization: making information available and accessible in a digital format 2. Digitalization: making processes more automated through the use of digital 3. Digital transformation: devising new business applications that integrate all the digitized data and digitalized applications 4. Emerging markets: new technologies create new markets 5. 3D Printing: production is revolutionized - A platform is the enabler of the connection between companies / stakeholders (ecosystem). Four types of platform  Exchanges  Transaction systems  Advertising-supported media  Hardware / Software standards - Properties of platforms  Distinct types of customers: the BM must serve different sides of customers  Direct interaction  Facilitating: interactions are facilitated through the platform - Network effects  Direct: increasing number or quality of customers drives an increase in value for the same type of customer (Facebook)  Indirect: increasing number or quality of customers drives an increase in value for customers on the other side of the platform (VISA holders and merchants) - Four key technological elements of platforms  Frictionless acquisition  Scalable growth: also through cloud computing  On-demand access and speed  Trust: authenticate customers - Symmetric competitors (similar value propositions, similar offerings, different customers, like BMW and MB) vs Asymmetric competitors (similar value propositions but different business models, like BMW and Uber) - Platforms’ business models  Pipeline model: based on subcontracting  Listing fee model  2-sided Commission Fee Model  Multi-Sided Commission Fee Model  Subscription Fee Model - Collaborative economy: economy built on decentralized networks and marketplaces that unlock the value of underused assets by matching needs and haves in ways that bypass traditional middlemen and disrupt centralized institutions - Sharing economy: voluntary lending, pooling, and allocation of resources and authorized use of public property but not contractual lending or leasing (NOwners)  Access-based consumption: rental, outsourcing, leasing without owning (Enjoy)  Peer-to-peer: private individuals organize P2P exchanges (BlaBla car, AirBnB)


4. Turn Data Into Assets - The challenge is to turn this data into useful insights - 5 principles for data strategy 1. Gather diverse types of data 2. Use data as a predictive layer in decision-making 3. Apply data to product innovation 4. Watch what customers do and not what they say 5. Combine data across silos - 3 myths: the algorithm will figure it out, spotting a pattern is enough, all the good data is big data - The Data Value Generated Tool generates strategic options for data initiatives  Area of impact and KPIs  Value template section  Concept generation  Data audit  Execution plan - 5 Vs of Big Data: Velocity, Volume, Variety, Veracity (recognizing qualitative), Variability - Organizational challenges of data  Embedding data skills set  Bridging silos  Sharing data with partners  Cybersecurity, privacy - The Big Data Business Model Maturity Model allows to understand at which point companies are, as transforming into big data driven companies is challenging  Monitoring: data and analytics to monitor the business  Insight: big data to uncover potential insights  Optimization: analytics to optimize key processes  Monetization  Metamorphosis

5. Innovate by Rapid Experimentation - An innovation is any change to a business product or service that adds value. To be an innovation, it has to be replicable at an economical cost and must satisfy a specific need - Digital technologies enabled a shift from innovation based on analysis and expertise to innovation based on ideation and experimentation (the process of learning what does and does not work)  Convergent experimentation: learning that eliminates options (MAKE CHOICES)  Divergent experimentation: explores options (CREATE CHOICES) - 7 principles of experimentation 1. Learn early 2. Be fast and iterate 3. Fall in love with the problem, not with the solution 4. Get credible feedback 5. Measure what matters now 6. Test your assumptions 7. Fail smart - MVP (Minimum Viable Product): development technique in which a new product is introduced in the market with basic features, but enough to get the attention of consumers. Not an option for every company. - 4 paths for scaling up 1. MVP roll-out 2. MVP launch: iterate very quickly as not able to limit the scope of the launch 3. Polished roll-out: limited locations and customers but not able to iterate quickly 4. Polished launch: innovation to all customers at once but not able to iterate quickly

6. Build and Adapt Your Value Proposition - The value proposition  explains who you work with and the value you provide  tells your audience what makes you uniquely different  aligns with what your target audience wants or needs - In the digital age, focusing only on existing and delivering the same value proposition is no longer sufficient - 3 routes out of a shrinking market (Ansoff matrix)  New customers, same value  New value, same customers (NYT online)  New value, new customers - Christensen theory: “job to be done offers a clear way to innovate” → C. defines job as “the progress that the customer is trying to make in a particular circumstance” and buys - hires - the product to carry out that thing - The Value Proposition Roadmap is a six-step process to map out new options 1. Identify key customer types by value received 2. Define current value for each customer 3. Identify emerging threats 4. Assess the strength of current value elements 5. Generate new potential value elements 6. Synthesize a new forward-looking value proposition 7. Business Model Disruption - Business disruption happens when an existing industry faces a challenge that offers a far greater value to the customer in a way that existing firms cannot compete with directly. It’s much more attractive than what the existing industry provides - Theories of disruption  Schumpeter: creative destruction, where new production units replace outdated ones (assembly line, internet)  Chistensen: the disrupter always start selling out to buyers who are outside the market of customers currently served by the incumbent - Features to be a disruptor: create something new that is affordable / available to anyone - Disruptive innovations vs Sustaining innovations - Innovator’s dilemma: successful companies when deciding whether to invest in disruptive innovations that may cannibalize their existing business or continue focus on their current offerings - Many of today’s biggest disrupters are not introducing a new fundamental technology, but they are applying established technology to the design of a new business model. Two sides  Value proposition  Value network - Three variables in business model disruption theory  Customer trajectory: are they already customers (outside-in) or inside-out  Disruptive scope: scope of the disruption  Other incumbents

8. The Nexus of Forces 1. Mobile 2. Social networks 3. Cloud 4. Information 5. Internet of Things  Network of physical objects embedded with electronics, sensors, and network connectivity that exchange data and are controlled remotely over the internet  Key features: Aware, Connected, Intelligent, Responsive  Smart, connected products have three components: physical, smart, connectivity  Can be grouped in four areas: Monitoring, Control, Optimization, Autonomy 9. Industrial Revolutions 1. First Industrial Revolution (1780)  From hand production to machines → steam engine  Driven by increasing demand, shortage of wood, abundance of coal, government’s support, cheap cotton by colonies  Railroads meant lower transportation costs, larger markets, and cheaper goods 2. Second Industrial Revolution (1870)  Expansion of rails and telegraph → movement of people and ideas  Innovations / Movements • Adam Smith’s Specialization • Fordism / Taylorism • Sloan’s Differentiation 3. Third Industrial Revolution (1969)  More demanding customers + New class of knowledged workers = tech, automation, microelectronics  Lean manufacturing (Toyota)  Emergence of agile manufacturing • Iterate faster • Flexibility • Bottom-up • Augmentation 4. Fourth Industrial Revolution  Modularization, Servitization, Co-creation, Co-production, Revolution of the digital industry, New cyber-physical technologies  Networked environment  Value co-creation: value not embedded in the product but as an outcome of interactions between customers (Lego) • Customer-centric orientation • Authenticity • Disintermediation • Characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres (AI, IoT, Robotics, Nanotechnology, 3DP)  Drivers of the 4th IR: velocity, scope, systematic impact 5. Fifth Industrial Revolution


10. Open Innovation and Start-Ups - Closed innovation (a company generates, develops, and commercializes its own ideas) vs Open innovation (a company commercializes both its own ideas as well as innovations from other firms and seeks ways to bring its in-house ideas to market by deploying pathways outside its current businesses) - Types of startups  Lifestyle startups: self-employed folks  Small business startups: family businesses  Scalable startups: born to be big  Buyable startups: born to be bought  Large company startups: innovate or die so create new products for new markets (Google)  Social startups


11. E-Commerce and E-Learning - Composed by different parts  Infrastructure  Presentation / Channels  Core functionality  Back office functionality - Barriers are security, trust, fraud, authentication, culture - Different types  Trade Pharma Network  C2B - Revenue models  Dropshipping  Retail  Private labelling  Subscription  Direct to consumer - Education 4.0’s supporting technologies  Blockchain  AI

This page was last edited on 11 March 2024, at 21:06
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