BEM 251 (MIS) MIDTERM (Lectures 2-6; Austin)
A/B Testing and Amazon
Discovered rentention rates increased if game was easier --> higher retention rates means higher ad rates A/B Testing: technique used to evaluate the efficacy of websites (control and variation→ which website gets better response?) A/B/n (multivariate testing) - you an add as many variations as you like, each needs to be designed separately Retention In quantitative terms, the retention on day X is the percentage of players of a given cohort that returned to the game X days after they started playing it. Amazon (online games) -A/B/n multivariate testing -Change in difficulty levels -Retention rates increased if the game was easier→ higher retention rates means higher ad rates and higher revenues -All about understanding consumer behavior
Engagement: a significant social media metric
Engagement anytime a user likes or comments - Higher consumer engagement is a sign of great content Engagement Rate: a metric that measures the level of engagement that a piece of created content is receiving from an audience. It shows how much people interact with the content. Factors that influence engagement include users' comments, shares, and likes = Engagement/Followers - Engagement rate good for assessing social media advertising campaigns; Can be applied to FB, twitter, and any other social media platform Good engagement rates FB: 1% (0.5%=avg.) Tweets: 0.02% Katy Perry 98 mil followers/ 0.7% Obama 88 mil Instagram: depends on time
IOT
Examples of stuff adding to it Proteus (digital health) - edible sensors tracking what you're eating, sends info to doctors, all uploaded somewhere Watson uses big data within IoT
Algorithms/ Google / Google Florida
Google -SEO -Scans web in advance, spider collects info about websites, search index with words -Ranking algorithm (pagerank links) -Machine learning (AI) → understand meaning of words Google Florida Really screwed over a lot of businesses right before Xmas, basically google's way of trying to keep the SEO playing field fair Changed SEO algorithms and metrics without telling people (high page ranks to low page ranks)
Closed Loop Marketing
Marketing that *relies on DATA and INSIGHTS from closed-loop reporting. "Close the loop" means that SALES TEAMS report to Marketing about what happened to the leads received*--> helps Marketing understand best and worst lead sources - For many, closed-loop reporting set up too hard/confusing to implement - *To be effective marketer*, though, need to be able to *tie every single lead, customer, and dollar, back to the marketing initiative that created them* --> how marketers prove their worth, and understand how to more efficiently reach their audience Closed Loop marketing vs. monetization of data Closed Loop marketing: Uses data to improve customer relationships; Indirect impact on revenue/profit Monetization of data: Sells the data they collect as part of their operations (facebook to Nike); data thought of as an asset (information); direct impact on revenue Closed Loop marketing: relating to Harras A way of keeping track of what individual customers respond to in order to return or visit other casinos: -Avoid using "gut instinct" by scientific testing of marketing strategies -3 changes in consumer behavior as driving force
Ch 1: The New CIO
*Backstory - Company* What business are they in? Loan operations (kinda like a Quicken loans) What is their industry position? • 16% market share • biggest competitor has 36% • next competitor has 15% Why is there a change in management? • stock price is down • prior CIO (Davies) didn't perform/had weaknesses Why did the stock price go down? • Not growing and not returning to bottom line • Stock price ↑ ; Revenue ↑ : Net Income ↓ * Backstory - Major 'Players' Key players: 1) Jim Barton: New CIO of IVK (former head of Loan Operations and a talented general manager) 2) Carl Williams - New CEO 3) Maggie Landis: Savy management consultant and gf, provides valuable insight, references, perspectives 4) The kid: Wise beyond his years, ~20, tech nerd, meets him at Vinnie's Bistro, proves useful sounding board and good advice (know what you don't know) 5) Davies - prior CEO o Lacks social skills (management level communication) o Didn't dress professionally o Didn't trust him with customers - tells barton he wont last a year 6) Bernie Ruben: Director of Technical Services Group and LONGTIME IVK employee, nearing retirement, doesn't give a shit ab risks to career. Provides Barton candid advice, knowledge, context he needs to make decisions 7) Raj Juvvani: Director of Cusomter Support Systems, Juvvani part of Barton's core IT team 8) Tyra Gordon: Director of Loan ops and New App Development Systems, worked closely with Barton in old position, takes lead on several new IT projects under his management 9) Paul Fenton: Director of Infrastructure and Ops, manages large & important domain, including IT security and is part of Barton's core IT team 10) Gary Geisler, Director of Planning and Control, works closely with Barton on IT financials 11) John Cho: Ivk's outspoken resident security genus, Cho has a distinct fashion sense and provocative musical talent 12) Jenny: Barton's ever-dependable executive assistant * Business Skills vs. IT Skills - IT management is about management; it positioned to understand business end to end, across departmental boundaries, better than everyone else - Push two circles together (vendiagram of "business smarts" and "Tech smarts" creating value in the middle) - count the value people and hrie them, - It leadeders, Execs, capability gap * The IT Roller Coaster - based on analysis of 3+ decades, described IT leaders job as roller coaster ride: fortunes and prestige of IT, and its leaders, swung wildly during this time, hight then low and back again and would continue to do so. During upcycles: tehcnologists seen as keeprs of the magic that enabled important progress Down cycle: it projects launched uring good years to chase rising demand became sources of unacceptible cost, demand vanished, ---> proejcts invested in chunks, cant really be switched off mid execution but sometimes do anyway
Ch 12: Communication
*Doctrine of Completed Staff Work take completed solutions to your boss, not questions about what you should do, only go when you understand everything and are confident in your solution, all boss needs to do is indicate approval or disapproval
Ch 2: CIO Challenges
* "Know what you don't know" Kid says: start figuring out who on team is really good @ what lots of managers dont know that/what they dont know (succeed mostly by managing appearance of success rather than actual this way^) - Accept that you don't know everything
Ch 19: Looking Forward
* Barton's options offered job as COO of larger company, maybe one day would be next CEO of IVK, hates idea of leaving his team, offered CIO job at company 10x IVK size by the kid -CEO at IVK → uncertain -COO at hero's company→ Robert Goldman (Earlington Financial Group) -CIO at kids company→ Jonathan Luce (founded Dazzle, computer graphics company purchased by mediaSpark and then Microsoft)
Ch 18: Managing Risk
* Business risk vs. Project risk business risk involves strategy, project involves execution and if you can actually pull this strategy off Business risk vs. Project risk Business risk→ strategy -Take risks, not sit back and minimize losses -Take risks and invest in mitigating it, buying insurance Project risk→ execution Risk escalator Risk escalator → risks speed up stairs; keep moving to stay in place
Business Case
- *Captures the reasoning for initiating a project or task.* Compelling business case: adequately captures *both the quantifiable and non-quantifiable characteristics of a proposed project.* How it is Presented: - Usually (1) a well structured written document - Sometimes in form of (2) short verbal agreement or (3) presentation Logic of the Business Case: - Whenever resources such as money or effort are consumed, they should be in support of a specific business need. Examples: 1) A software upgrade might improve system performance, *but the "business case" is that better performance would improve customer satisfaction, require less task processing time, or reduce system maintenance costs* (need). Can be comprehensive and highly structured, as required by formal project management methodologies or informal and brief. Info in formal business case could include: - background of the project - expected business benefits, - options considered (with reasons for rejecting or carrying forward each option), - the expected costs of the project, - a gap analysis and the expected risks. **Consideration should also be given to the option of doing nothing *including the costs and risks of inactivity.* - From this information, the justification for the project is derived. Note NOT job of the project manager to build the business case-->usually responsibility of stakeholders and sponsors.
Granularity of Data
- Detailed data; the lowest level of data in a dataset; small as possible pieces in order to be more defined and detailed - Refers to how detail-oriented a single field is. - Example: how a name field is subdivided; if it is contained in a single field or subdivided into its constituents such as first name, middle name and last name. *As the data becomes more subdivided and specific, it is considered more granular*. ADVANTAGE of granular data: - Can be molded to fit data scientist or analyst needs - Can be aggregated and disaggregated to meet the needs of different situations. - *Granular data can be easily merged with data from external sources and can be effectively integrated.* When Data is NOT granulated: - such as a name or address field being saved as a whole = difficult to analyze because in large chunks MOVIEPASS - hopes pinned on potential of user data to sell advertisements and help drive box-office revenue, allowing company to strike revenue sharing and bulk ticket deals with studios and cinemas idea trying to be monetized: was really about making money on advertising to studios, on data, on guaranteeing the box office Examples of granular data: - know what time people go to the movies - what genres they like - certain people go to AMC/Regal etc - Different viewing habits they have across all channels Trying to diversify revenue stream use MoviePass brand and platform to push people to theatres to see if its co-owned films, reap share of box office profits, create greater potential downstream revenues on streaming, dvd, and demand sales
Blackrock Robo Investing
- Investing in robots that can make better/faster use of data to predict where people should put their money - reposition some stock funds, adjust fees, streamline research as part of overhaul of its stock-picking unit - rely on robots vs humans on what to buy and sell - adopted view that difficult for humans to beat market with traditional bets on large US stocks --> will create job losses, price changes, ad greater ephasis as computer models that inform investments - better position to be competitive longer term and take advantage of blackrock's scale
Machines can do that too article
- Machines can do that too --> clothing being made for you, - most jobs become partly automated in growing parts of industry where high powered algorithms roam free, however it is the machine, and not the buyers gu, that often anticipates what customers want byers and merchandise planners for store inventory may be affected by alforthims First algorithm generated random images it tried to pass off as clothing, second distinguished between those images and clothes in inventory --> the back and forth managed to create designs whose sles are now growing at 100% -Stichfix: relies on algorithms/big data (less on intuition) to guide its buying decisions --> project how many clients will be in a given situation or state, several months into the future (like expanding wardrobe after starting new job), and people know which styles people with different profiles tend to favor (i.e. petite nurse with children who lives in texas) - online wish lists, online ratings, recent purchases also help them know what to add to stock Bureau of Labor Statistics: expects employment of wholesale and retail buyers to contract by 2% over a decade, versus 7% increase for all occupations. (automation of less sophisticated tasks or less stylistically demanding retailers like auto parts)
Data is the biggest resource grab in history
- Oklahoma Land Rush 1893 Sooners - Comparison to Google, Amazon, uber, fb, tesla
Apples 1 Trillion milestone article
- Products have Reshaped life - 1.4 billion iphones sold since 2007
5. Monetization of Data & Ethics of Data Collection
- Using data for quantifiable economic benefit - Can be INDIRECT methods i.e. measurable business performance, bartering, productizing information (new info-based offerings), informationalizing products (including info as a value-added component of an existing offering), - OR selling data outright (via a data broker or independently) 1) Example: Facebook (monetize data) Monetization of data→ marketing of data Sell data that they collect as part of operations Data as an asset 2) Example: What your Car Knows About You - Autocompanies gathering real-time data tracking where car located to how hard its breaking to whether windshield wipers are on Uses: - can use data to craft targeted in-car ads (fuel low, ad for near by gas) - sell data to mapping firms looking to provide more accurate traffic info, etc. - insurance companies - GM, through Marketplace app, uses in car delivery (location + keyless entry feature) for amazon packages - contracts with companies and municipalities about vehicles used in fleets - McKinsey and Co --> estimates monetizing data from connected cars worth ~750 billion by 2030 3) Example: Target, catalogs (phone, gmail) - Analyzed data for patterns, found ~25 products that when analyzed together allowed him to assign shopper a pregnancy prediction score, and due date within a small window, specifying timing of which pregnancy coupons to send when, --> realized they needed to spread the coupons to seem random because it freaked people out if too targeted - this kind of data gathering = inevitable unless all purchased in cash
Disruptive Technologies
- innovative forces that include a different set of attributes than those valued by mainstream customers - "Disruption" is the new normal - A technology that significantly alters the way that businesses operate. A disruptive technology may force companies to alter the way that they approach their business, risk losing market share or risk becoming irrelevant. 1) Disruptive Technologies do NOT have to be BRAND NEW technologies 2) Disruptive Technologies can be "OLD SCHOOL" business concepts delivered in a "NEW SCHOOL" way 3) Disruptive tEchnologies usually destabilize multiple industries 4) Disruptive technologies can Present less than obvious opportunities Examples: Amazon KINDLE Buying books online Impacts: newspapers, magazines, publishers, paper/lumber, retail bookstores, authors, writing agents, printing, type setters, clerks, literary agents Jobs affected: type setter Borders/bookstores close Uber Changed the way we think about transportation Disrupted commerce: Auto industry supports one of every jobs in the U.S.;90% time the car is not used WINNERS: 1) Netflix - Innovation: Pioneered streaming video services; $6B Revenue 2014 2) Uber (automotive industry disrupter) - Innovation: Pioneered digital ride-sharing Result: $10B revenue (2015) 3) Amazon - Innovation: Pioneered eCommerce platforms Revenue: $89B (2014) LOSERS 1) Blockbuster Mistake: didn't adapt to video streaming --> BANKRUPT 2010 2) Kodak Films Mistake: didn't adapt to digital photography (bankrupt 2012) 3) Borders - Didn't adapt to eCommerce (bankrupt 2011) *Using stats + data = all about finding inefficiencies in Markets
Now advertisers can watch you watch tv
- using Crowd emotions EQ platform, broadcaster can find out what an audience thought about program instead of being falsesly skewed by respondents trying to give right answer state department scientists TVvision: company that measures eyes on screen -facial recognition technology
IBM Watson
-Analyzes unstructured data -Understands complex questions -Learns human constructs like language, culture, and context - dominated best jeopardy players at the time
Ch 9: IT and the Board of Directors
1) Board's responsibility for IT risks - Ask the board to take a greater responsibility and become more involved in IT - Boards can face huge liabilities from lack of IT involvement 2) Responsibility vs. Ignorance -Cannot claim ignorance -Active and visible support of IT vs. "stay in the basement" attitude -"I don't know much about IT" → lead to criticism of board - IT risk mostly invisible to managers until it goes wrong - More involvement and oversight 3) Individual decisions, incremental vs. cumulative risks -Risk is the emergent result of countless incremental and individually harmless decisions -Decision to take a shortcut in how a program accesses a database to make response time better -Decision to leave until later standardization on networking technology -Individual mistakes pile up (accumulate and create big issues; cumulative risk)
Ch 10: Crisis
1) DoS attacks - Denial of service, flood website with transactions, overload it with useless traffic - not unusual but this one coming from too many locations, ex: I love you bug - Floods servers with useless transactions so that consumers cannot get in - Customer service down 2) Internal vs. External attacks 3) IT risks vs. Business (customer) Decisions IT risks: - John Cho wanted funding for security, Barton previously shut him down when head of Loan Ops - Exploited security hole - Compromising IT security - Supposed to create careful records of all files introduced into production, but haven't - Operate under pressure from customer; quick changes -Business trade-off→ customer happy, but not following proper procedures (security) Security options Shut down and wipe servers or create a parallel system (backup could cause same problem)
Ch 5: Value of IT
1) How to Value IT Services Inside a Company -Not a profit center (could not point to growth in revenues or profitability) -IT created value for its internal customers, the business units -IT-enabled change results in savings→ value? -Value from it can arise from its ability to give a firm capability that sets it apart from its rivals (Zara) 1b) IT Doesnt Matter- Nicholas Carr -IT has become such a commodity that Investments in IT could not be counted on to provide capabilities that were not also accessible to competitors -It is not the IT that is causing competitive differentiation, but the way IT is used and the success with which it is adapted within the company culture -Maybe applied to word-processing software, but not newer (old news) 2) Commoditization of Technology Almost total lack of meaningful differentiation in [products or services]; thin margins and are sold on the basis of price and not brand. This situation is characterized by standardized, ever cheaper, and common technology that invites more suppliers who lower the prices even further. - Everyone has IT (does not provide competitive advantage) - Sometimes invest in an IT project with no expectation that it will provide a competitive edge → do it just to stay in business - Invest in It because competitors are to avoid 'strategic jeopardy' (necessary cost) → valuable because might not have business without it 3) Moore's Law: Definition: the cost performance of computers doubles every 18 months or so; for the same computer performance, the cost halves every 18 months Practical: - applications of new technologies not economically feasible just a few years earlier become economically feasible - Stay on top of emerging technologies and changing economies of them - Build IT in flexible manner that allow incorporation of new technologies 3a) Legacy systems problem - inflexible technology 4) Competes vs. Qualifiers - Qualifier: keeps you in business; qualify puts you at the starting line - Compete: gives you a potential edge over other companies in your industry; help you win the race - competes will eventually become qualifiers, due to commoditization 4b) Competes vs. Qualifiers cycle - Systems in compete category move to qualifier category as competitors copy - Over time, compete gets smaller and qualifier category gets larger (unless add competes faster than old ones become qualifiers)
Ch 4: Cost of IT
1) IT Cost Allocation Systems (Methodologies) - *IT expenses→ first based on phones and email addresses at IVK* - *IT department formally controls none of the budget that gets spent on IT; the business units get budget allocated to them for IT expenditures, then IT charges them for their services, using an internal pricing system* - Chargeback system: Service provider to the business units→ charge costs back to business units (billing for hours and overhead→ formula cost of resource used) - overhead chargeback :70-80% - Bartons simplified chargeback costs assigned to services and departments charged for services IT cost % 8% of sales (historically 5-6%) ~29 million, not including whats spend on mobile devices, on IT (cash flow) and ~ 18.5 mil on accrual ~8% of sales on IT *3 mapping chargeback* -IT costs -IT services -chargeback *Evolution of IVK's application portfolio and infrastructure* -Founding: A/P= 90%; Infrastructure= 10% -Now: A/P= 40%; Infrastructure= 60% -Future: ?? service-based architecture; data analytics; real-time operations *IT Promise Greater Than Reality* -Business analytical capabilities are an area where hype has outpaced reality -Plenty of great things possible, but have to be careful and smart with investments -Must make effective use of results of analysis -It will be a while before IT systems in companies eliminate the need for good managers "business units get budget allocated to them for IT expenditures, then we charge them for our services using an internal pricing system in some cases they also can use budget to obtain services from external providers, though limits placed on that in the past to make sure we offset all of the fixed cost associated with IT salaries and infrastructure" --> IT billed out, - also IT like services such as serivce and support for mobile devises provided by external services that LOBs procured on their own, using their own non-IT budgets
Ch 3: CIO leadership
1) IT Management is about Management - Skill and talent management/key skills, key contributors 2) "Know what you don't know" - Know what you dont know "KWYDK" - You wont last one year "YWLOY - Ruben helpful 3) How to manage IT staff a) know who your people are b) be able to supervise them c) know what they are doing - Very talented→ bring right people and trust them (Work in their own ways) - Know key people and how to supervise them - Hard to manage - Sidekicks
Ch 15: Managing Talent
1) Managing IT personnel: time vs. talent - Some IT personnel much more productive - Tough to manage; Skill sets are rare - Ivan (best guy) assigned project, but working on his own political agenda at work (but extremely talented) - Put up with things (as leader) from best people (how they retain them; John Cho in jazz band) - Don't want to buy time from people, want to buy smarts, resourcefulness, good business judgment, new ideas; hard to measure
Ch 6: Project Management
1) Scope Creep Because there is a failure to establish clear requirements of business users at the beginning of a project, often project managers find themselves under pressure to deliver in excess of what was originally agreed --> Project grows and changes - confront by clearly defining every time with client 2: Fail Forward/Fail Fast Go on with making messes so that we can deal with them sooner rather than later (inevitable mess) → better to have them sooner rather than later 3) Defining IT Project Requirements Anticipating requirements Unexpected things happen 4) Agile Management -Divide projects into smaller chunks--> and see what happens, if it fails its less costly because only small part fails -Short-cycle, iterative, and feature-driven -Projects that are exploratory in nature, ones that push the envelope of schedule, risk, and rewards -Monitor and adapt -Cannot anticipate problems - envision, speculate, iteratively deliver features, monitor and adapt, close, good for high exploration-factor projects, projects where customer responsiveness is paramount, or orgs with innovative cultures 5) TPM, Agile Management vs. TPM - traditional project management - lay everything out in advance, defining concrete tasks with stated durations, more planning than managing focused - Planning techniques and methods→ Gantt charts, PERT, CPM, resource scheduling - Managing problems CAN anticipate (planning) 6) Death March Projects - Project with a bad plan that managers are determined to stick to - Adds no values to career or skill set - Yelling a lot, making people work longer and longer hours - Never ends - don't want to hear about unexpected problems, low morale, catastrophe often at end
Lecture 2: Learning Objective
1) Understand how the concepts of business case and monetization apply to all the companies. 2) Understanding how the concept of granular data applies to Moviepass. (i.e. do NOT concern yourself with trying to apply the concept of granular data to Nike, McDonalds, Facebook, or Kodak) Concepts: 1) Business Case: 2) Monetization 3) Granular Data Companies: 1) Nike 2) Mcdonlads 3) Facebook 4) Kodak 5) Moviepass
Ch 7: The Runaway Project
1a) Runaway Projects out of control, over budget, and behind schedule -Keep getting bigger and bigger (never starts) 1b) IR project: -Replace middle and back-end systems; form cross-functional team with equal parts of business and IT staff, led by business manager; best people on project; cost=3% current revenues -1.5 years, Unmotivated leader, Overwhelming, not IT members (cannot reasonably evaluate Netifex), lack of technical expertise 1c) Netifex -Vendor being pay every month for IR project -No concrete benefits -Disconnect → offshore contractors; Expertise in Unix-based technologies (IVK works with competing Microsoft) 2) Paralysis of Analysis project gets too big, get all psyched to tackle it then look at it in earnest and it seems impossible, overanalyze, never launches, waste of money -Trying to take on too big of a project -Project going sideways -Spending a lot of money, but no improvements
TOP 5 publicly traded companies by market cap
2001: 1) GE: 406mil 2) Microsoft @ 365 mil 3) Exon @ 272 mil 4) Citibank @ 261 mil 5) Walmart @ 260 mil 2006: 1) Exxon @ 446 bil 2) GE @ 383 bil 3) Total (oil and gas) @ 327 bil 4) Microsoft @ 293 bil 5) Citibank @ 273 bil 2011: 1) Exxon @ 406 bil 2) APPLE @ 376 bil 3) PetroChina @277 4) Shell @ 237 5) ICBC (bank) @ 228 2016: (almost @ faang) 1) APPLE @ 582 BIL 2) GOOGLE @556 BIL 3) MICROSOFT @ 452 BIL 4) AMAZON 5) FACEBOOk (AAGFN) FAANG MARKET CAP US TRILLIONS 1) Apple @ ~1.1 2) Amazon @ ~1 3) Google @ ~.9 4) Facebook @~.5 5) Netflix @~.2 - accounts ~50% of gains achieved by S&P 500's stock index auto + disney + exxon combined not even at google level yet - economists starting to look at rise of superstar firms constributing to lacking wages, shrinking middle calss, rising income inequality in 1975 109 companies collected half of profits produced publicly, now just 30 companies - power for these companies highest its been since 1950 - more than 3/4 of american industries grown more concentrated since 1980 - today almost half of assets controlled by 5 banks, - 6 airlines --> 3 - 4 companies control 98% wireless market
Disney Timeline
2005 - Bob Iger Appointed CEO 2006 - Pixar 2009 - Marvel 2011 - NGE Project Begins 2012 - Lucas Films (starwars) 2013 - NGE Project Debuts (stock starts going much higher)
Can machines think?
ALAN TURING: "the original question, can machines think, i believe to be too meaningless to deserve discussion" - designed first computer in ENGLAND during WWII - Part of top secret project to break coded messages sent by germans - @ end of war, honored for his work in helping it end - 1945 recruited by England's national physical lab to create an electronic computer - The imitation game film Structured data (TIP OF ICEBERG) vs. unstructured (WHOLE BERG) - Unstructured examples: streaming music, videos, voicemail messages - STRUCTURED data doesn't take up a lot of storage space, its easy to deal with, find, retrieve, ---> NOT the case for UNSTRUCTURED
Amazon & Wholefoods
Amazon & Whole Foods Data and product Data: Correlations between purchases of different products and categories Product: Differentiation, Best shopping experience, delivery, prices and products Understanding consumer even further Want to have the whole pie, not share
Switching Costs Examples
Apple Music Gives away 3 month trial to compensate for overcoming obstacles of switching--> (like how if you switched from spotify the fact that you cant automatically have all your old playlists) Using switching cost as strategy 3-month free trial→ build library and do not want to switch Harrah's switching: data customizes/tailors to customer, get offered all these unique things they dont want to go anywhere else because it feels like a personalized experience/relationship -Collect data on customers -Send coupons to lure them back based on what they like (see what works) -Customers pulled back in because of info -Maintains data on customer preferences, easy to lure a customer back Amazon & Whole Foods switching Amazon prime→ free quick shipping/student discounts→ get hooked (50% online market) Amazon & Whole Foods data -Data as a switching cost i.e. once they collect enough data about you, can provide preferences, ease, makes switching from them difficult - everyone buys food and that leads to a lot of data collection -Correlation between groceries and buying patterns of other goods -Grocery buying habits and patterns. Preferences. Correlations between purchases of different products and even different categories -Collects data/customer preferences makes switching away difficult
LECTURE 5
Concepts/Definitions: Transactional Businesses vs. Relationship Based Businesses Closed Loop Marketing Switching Costs Data as a Switching Cost Companies: Harrah's Disney Amazon/Whole Foods
Lecture 3:
Concepts: 1. Horizontal vs. Vertical Integration 2. Data as Part of the Supply Chain 3. Data and Vertical Integration 4. Technology and Branding 5. Monetization of Data 6. Ethics & Data Collection Companies/People Zara Toy Makers Kindle Taylor Swift The Grateful Dead (up and coming artists) Car Makers Uber
Switching Costs
Costs consumers incur when they switch to new or different products or services (result of changing brands, suppliers, products) - Although most prevalent switching costs are moentary in nature, ALSO psychological, effort- and time-based switching costs Data as a Switching Cost Amazon Harrah's
Customer Relationship Business
Customizing the offer; Tailoring the message - Right offer, right message, right time CYCLE: (circle) 1) Define: objectives, tests, control cells 2) Customer treatment 3) Execute 4) Customer Action/Non-Action 5) Track 6) Measure: Profit & Loss, behavior change, new test report 7) Learn Customer Relationship Life Cycle - Establish --> Strengthen --> Reinvigorate
2. Data as Part of the Supply Chain & 3. Data and Vertical Integration
Data gathering (Structured or unstructured) is now part of the supply chain - Zara = STRUCTURED Data - Gaming (Zing) = UNSTRUCTURED Data - Companies incorporate data gathering into the business improvement and/or business development process Examples: Zara: FAST Fashion 1) Zara Stores: Store manager notices certain dress selling well, use customized handheld device to regulary send new orders via internet to Zara's headquarters; calls in suggestions for new colors and cuts 2) Zara HQ: Designers and product managers receive info, match it with suggestions from other Zara store managers 3) Zara HQ: Designers then draw up new styles and send patterns to Zara factories in Spain, where workers cut, dye, and stitch together the clothes 4) Zara Factory: Clothes move through Zara's distribution center and reach stores within 48 hours Zara Model & Strategy 1) SUPER RESPONSIVE buyer driven supply chain - customer main force behind Zara brand 2) QUICK design-to-distribution process - Max time from conception to distribution center = 3 weeks 3) ZERO ADVERTISING - very low spending on marketing while high spendingo n stores 4) Vertically Integrated SIMPLE BUSINESS IDEA: *links customer demand to manufacturing, and link manufacturing to distribution. Toy Makers: - Nickelodeon Slime - Zing Thumb Chucks - Finding trends on the internet, then quickly putting together new games for new trends
Disney: NEXT GENERATION (nge)
Disney 2011: Speds $1B on NGE Disney: Why spend on Next Generational Experience? -Disney was on the verge of becoming "dangerously complex and transactional" (need to get back to relationship based business case!) -Iger brought it back to the original business strategy/case (Relationship based→ get to know consumer and create a relationship/loyalty) Disney Problems Parks full of complications→ retention, long lines, overcrowded, bottlenecks and backups MagicBand electric ticket band the registers consumer data and flow (stop delivering a one size fits all experience) NGE UPSIDE: Direct revenue impact: -Kids accessorizing MagicBands with Frozen-themed tchotchkes: -Disney's PhotoPass, photos and videos tied to MagicBand Indirect: - Collecting massaive amounts of customer data NGE Downside: - not implemented in other parks, Anaheim and Shanghai (Technological Obsolescence) - $1b Investment- Did not fully deliver on its "Massive Expectations" Disney stock still quite high (higher than pretty much ever before since around 2014) @ ~$112
Disney and Harrah's similarities
Disney and Harrah's similarities -Customer data and tracking -Individualize marketing -Knowing customers, giving them great service, and rewarding loyalty -Customer relations/ focus on consumer
Harrah's
Harrah's - Gary Loveman understood how to analyze data and turn info into meaningful strategy (taught Service Manaement and developed interest in service/customer service industry; coauthored paper "Putting Service Profit Chain to Work" --> began consulting for Harrah's --> Offered COO position) - Harrah's Known as the "friendly casino" where customer names were remembered -Took company public in 70's First purely gaming company on the NYSE -Focus on customer comfort, fair games, ensuring customer enjoyment Harrah's Closed-loop marketing model: - Act and adjust: what do we need to do differently? 1) Define: Campaign objectiveness & Test Outcomes 2) Execute: Marketing Campaign 3) Track: Linked Transactions 4) Evaluate: Campaign Effectiveness 5) Learn & Refine: Campaigns & Approaches Main difference: - Used database marketing and decision-science-based analytical tools to WIDEN gap between them and other casinos that mainly used intuition in determining customer incentives -Predict the value of a customer -Market based on that expected value -Track transactions linked to marketing initiatives -Evaluate the effectiveness -Track profitability Refine Marketing Approaches (marketing to direct consumer→ individualized); Monitor what customer responds to using customer analytics (total rewards program);Use database marketing and decision-science-based analytical tools (differentiate) Harrah's Results: 1) Corporate Earnings DOUBLED in 1 yr 2) 72% IRR on Investments Technology 3) Same-Store Revenue Growth of 14% (first year) 4) Rise in Stock Price 5) Creation of a Harrah's Brand in the Gaming Industry *attracted customers via DIFFERENTIATION of the things they offered them, to customize experience to meet individual customer needs* *used data to build customer relationship*
1. Horizontal vs. Vertical Integration
Horizontal→ Expands out (into other products/services/lines) Vertical→ Expands down/up (provides greater control over supply chain); creating more money from the existing product one has, and continues to use. Examples of HORIZONTAL integration: 1) Rovac Batteries becoming -->Spectrum Brands - Rovac was distant 3rd in market share, market dominated by top 2 players, no chance to improve position with that product - Leveraged distribution network Examples of VERTICAL integration: - Ice-cream shop owner: buying/ building ice-cream facility, buying dairy farms to grow original product - Zara: highly vertically integrated, super responsive "Grow or die. ifyou want to innovate dont focus on the results" - Ortega, --> focus on process of product not results - Yankees: YES Network significantly increases value of the NY Yankees and helps George Steinbrenner to outspend all the competition [to obtain better players] --> Steinbrenner gets Yankees TV contract (YES network)-Broadcast games and take revenue Increased value of network Vertical integration: controlling supply chain-cost and revenue
MAGGIES NOTES on "IT Manager as a Business Leader"
MAGGIES NOTES on "IT Manager as a Business Leader" Barriers that prevent IT managers from becoming business leaders; 1) IT managers lack business skills and competencies 2) Business leaders fail to udnestand importance of IT or misperceptions of it management role as the orgnaizations information plumber 3) IT distance from customers and customer experience 4) It managers lack time to spend on strategic issues 5) IT managers often left out of enterprise digitization discussions in other parts of company 6) ITs poor collab w lines of business 7) lack of support from CEO/board 8) insufficient authority or responsibility given to IT *Vast majority of top IT managers said they sought a more strategic role, a greater role in making or shaping strategy* Global Shifts Affecting IT management role: 1) most comapnies foused on using IT to increase market share, moving beyond past emphasis on cost cutting 2) proliferation of options for sourcing IT services "pff premises" Maggie's Input based on presentation regarding the changing CIO role • Enhancing / maintaining relationships with other business leaders • Ability to develop an organization of talented technologists who understand business • Ability to educate CEO and peer executives o new possibilities by digital technologies o key business trade-offs implicit in tech choices • ability to clearly express a compelling vision for the digitized future of the enterprise
Memes
Memes an idea, behavior or style that spreads from person to person within a culture (know human interaction and behavior→ something going viral) Memes are ideas that are imitated because they strike a common chord and increase the likelihood of evolutionary survival. Meme Theory: First proposed by Richard Dawkins in "The Selfish Gene" over 30 yrs ago PIZZA HUT: -Move to a digital focus→ 50% more orders -Focus on how they are communicating and engaging with consumers -Get message out on popular channels -Partnered with influencers to talk about their product on social media and create buzz GUCCI -Leverage social media -Launch a Meme Campaign (memes are usually incidental/coincidental?) Very expensive, Drew attention -First well-known attempt to generate memes from ads -Success or failure? Hard to say→ Got the name out more, but random posts like Fashion Week, had the same efficacy - Highest engagement was with Rapper Schoolboy Q's daughter wearing pink Gucci suit to grammy's AMY AND SHELDON: -Items of gossip are like living things that seek to reproduce -Exponentially increases -A/B testing (1 story vs. another)
Companies - business case examples
Nike (business case) Bill Bowerman believed there was a market for a better running shoe McDonalds (business case) Americans would eat fast food Facebook (Business Case) Connect people 20th Century Fox/ Star Wars (Business Case) These movies are no longer working. Better: People will always love these movies so there is a market for them Kodak (Business Case) Don't move forward with digital photography because it cuts into our main business
SEO & SEO Metrics
Search Engine Optimization methodology of strategies, techniques, and tactics used to increase the amount of visitors to a website by obtaining a high-ranking placement in the search results page of a search engine (SERP) → google, yahoo, etc. Downside to SEOs: people try to game/manipulate the system for monetary benefit and sometimes can SEO METRICS: 1) Retention (on-line games): In quantitative terms, the retention on day X is the percentage of players of a given cohort that returned to the game X days after they started playing it. 2) Sticky Websites: The site makes people want to stay on it and/or come back regularly. 3) Click through Rates: How often users click through from the search results. 4) Conversion Rate: The percentage of website visitors who take a desired action — filling out a form, buying something, or joining/becoming a member, etc. Illicit Tactics - Artificially Improve Page Rank: 1) Keyword Stuffing: loading a webpage with keywords in an attempt to manipulate a site's ranking in search results. 2) Hidden/Invisible Text: (when search engines were much less sophisticated) hiding text on webpages. Also, hiding links on other websites linking back to the page you wanted to gain ranking. 3) Hidden Links: Links added on sites owned by the same company, or owned by a partner that has predefined this relationship. Also, sites are illegally hacked to be able to add the links. Organic vs. Inorganic Organic not paid Inorganic Searches paid Social Media--> death of SEO? Some internet authorities thought it would be
4. Branding and Technology
Taylor Swift vs. Grateful Dead - Grateful dead was fine with people recording videos of their concerts because they wanted people to see what a great time they were having, and wanted their main revenue source to be from fans attending their concerts Strategies: (with apple music example) 1) Grow your brand - Up and coming musician or artist (give away content to build a following -give away content to build a following (Grateful Dead→ let others come to concerts for free and record music (give away content to make brand, create fun atmosphere and get word out) 2) Protect your brand (t-swift/ established artists) - Established artists (don't give away content --sustain your base) -Royalties -Protecting her own brand -Album vs. Streaming business→ harder for artists to make money 3) -Trash brand: Mike Jeffries/Abercrombie & Fitch (ignore technologic shifts in your industry) Abercrombie & Fitch -Original brand→ hunting and fishing equipment -Mike Jeffries (CEO) -Changed A&F -Lost touch with the market→ insulting comments, exclusionary, missed online opportunity "The world has changed and he hasn't" (arrogance) -Did not understand technological world
Technological Obsolescence
Technological Obsolescence products go out of date/disappear When a technical product or service is no longer needed or wanted even though it could still be in working order. Technological obsolescence generally occurs when a new product has been created to replace an older version Examples of Technological Obsolescence Ex: Disney's MagicBand was unnecessary in Shanghai because everyone has iPhones Ex: answering machine, typewriter, CD player, Kodak camera, GPS on dashboard
Transactional Based Business
Transactional Marketing is a business strategy that focuses on single, "point of sale"transactions. - Emphasis on maximizing EFFICIENCY and VOLUME of INDIVIDUAL SALES *RATHER than developing a relationship* with the buyer Transactional vs. Relationship Transactional making the immediate sale; as many sales in the short period Relationship-based marketing making customer relationships and creating loyalty; long-term goals; understanding consumers needs and wants
3 V'S OF BIG DATA
VOLUME: - Terabytes - Records - Transactions - Tables & Files VARIETY: - structured - unstructured - semistructured - all the above VELOCITY - batch - near-time - real-time - streams
Disney Walt, History, Trouble
Walt Disney initial strategy: - multiple parts working off each other (everything connected): films/creativity/ theatrical idea of films/idea at the center --> how you get someone in the door then other things follow (theme parks, merchandise, music, publishing, and TV) - Each part provides content and drive sales for the others (new content→ Pixar, Marvel→ fit business plan) Trouble @ disney: 1) Walt dies in 1966 2) Company strays from original business model--> fewer animated films (only 12 fully animated features from 60s-80s) 3) Plugged gap by reissuing older films: Cinderella, lady and tramp 4) 1984 - BOB EISNER appoitned as ceo (tries to diversify disney --> disney struggles even more) 5) 2005: Bob Iger appointed CEO Jim McPhee (disney parks vp): "disney world was on verge of becoming dangerously complex and transactional"
Network Effect and Network Effect Hurdle
What is the 'Network Effect'? A phenomenon where increased numbers of people or participants improves the value of a good or service (i.e. Internet, FB,) - When few users: not very valuable to anyone (i.e. internet only to military and research scientists) - as users gained access to the internet, adding more content, information, and services, --> more value The 'Network Effect' Hurdle: - The chief hurdle for any good or service which uses the network effect is *to get enough users initially so that the network effects take hold*. - *Amount of users required for significant network effects = critical mass.* - After the critical mass is attained, the good or service should be able to obtain many new users since its network offers *utility*.
IOT
global network of machines and devices capable of interacting with each other - basically connecting any device with an on and off switch to the Internet (and/or to each other). includes: everything from cellphones, coffee makers, washing machines, headphones, lamps, wearable devices and almost anything else you can think of. - also applies to components of machines, for example a jet engine of an airplane or the drill of an oil rig. on off switch --> part of IoT Gartner says that by 2020 there will be over 26 billion connected devices... That's a lot of connections (some even estimate this number to be much higher, over 100 billion). *The IoT is a giant network of connected "things" (which also includes people). The relationship will be between people-people, people-things, and things-things.*
Monetization
the process of converting something that once was free into a product that is sold (- the process of turning a non-revenue-generating item into cash) - establish an asset or object as legal tender. - any form of revenue generation - The term "monetize" has different meanings depending on the context. E.g: Governments monetize debt to keep interest rates on borrowed money low and to avoid a financial crisis, *while businesses monetize products and services to generate profit.* - web dev: ability to generate revenue through your website or blog Nike --> celebrities marketing/ wearing their shoes; manufacturing in japan Mcdonalds --> land ownership facebook --> data mining, ads, target marketing (sheryl sandberg) kodak --> failed to monetize digital idea Failures: 20th Century Fox/ Star Wars (Monetization) Sell merchandising rights for Star Wars to George Lucas for $20,000 (should have got merchandising rights!). Today merch rights over $3 bill Kodak (Monetization) Continue doing what we do and selling film cameras "that's cute, but don't tell anyone about it" (Apple clips kodak)