The Data Asset
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Visit this link to complete the quiz - https://mix.office.com/watch/ays9xktksvjb The Data Asset Introduction - Databases, Business Intelligence, Analytics, Big Data, and Competitive Advantage
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The Data Asset
- 1. THE DATA ASSET INTRODUCTION - DATABASES, BUSINESS INTELLIGENCE, ANALYTICS, BIG DATA, AND COMPETITIVE ADVANTAGE
- 2. INTRODUCTION 1. Understand how increasingly standardized data, access to third-party data sets, cheap, fast computing and easier-to- use software are collectively enabling a new age of decision making. 2. Be familiar with some of the enterprises that have benefited from data-driven, fact-based decision making.
- 3. INTRODUCTION • Big Data • Big data is a general term used to describe the massive amount of data available to today’s managers. Big data are often unstructured and are too big and costly to easily work through use of conventional databases, but new tools are making these massive datasets available for analysis and insight. • Business Intelligence (BI) • A term combining aspects of reporting, data exploration and ad hoc queries, and sophisticated data modeling and analysis.
- 4. INTRODUCTION • Analytics • A term describing the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions. • Machine Learning • A type of artificial intelligence that leverages massive amounts of data so that computers can improve the accuracy of actions and predictions on their own without additional programming.
- 5. INTRODUCTION • Data • Analytics • Competitive Advantage
- 6. INTRODUCTION Major League Baseball’s At the Ballpark app will use iBeacon technology to distribute deals and guide y Source - http://www.technologytell.com/apple/130140/mlb-utilizing-ibeacon-technology-in-ballpar
- 7. INTRODUCTION • What have we discussed? • The amount of data being created doubles every two years. • In many organizations, available data is not exploited to advantage. However new tools supporting big data, business intelligence, and analytics are helping managers make sense of this data torrent. • Data is oftentimes considered a defensible source of competitive advantage; however, advantages based on capabilities and data that others can acquire will be short-lived.
Editor's Notes
- LEARNING OBJECTIVES Understand how increasingly standardized data, access to third-party data sets, cheap, fast computing and easier-to-use software are collectively enabling a new age of decision making. Be familiar with some of the enterprises that have benefited from data-driven, fact-based decision making
- The planet is awash in data. Cash registers ring up transactions worldwide. Web browsers leave a trail of cookie crumbs nearly everywhere they go. Fitness trackers, health monitors, and smartphone apps arecollectingdataonthebehaviorofmillions.Andwithradiofrequencyidentification(RFID),inventory can literally announce its presence so that firms can precisely journal every hop their products make along the value chain: “I’m arriving in the warehouse,” “I’m on the store shelf,” “I’m leaving out the front door.” A study by Gartner Research claims that the amount of data on corporate hard drives doubles everysixmonths,[1]whileIDCstatesthatthecollectivenumberofthosebitsalreadyexceedsthenumber of stars in the universe.[2] Walmart alone boasts a data volume well over 125 times as large as the entire print collection of the US Library of Congress, and rising.[3]It’s further noted that the Walmart figure is just for data stored on systems provided by the vendor Teradata. Walmart has many systems outside its Teradata-sourced warehouses, too. You’ll hear managers today broadly refer to this torrent of bits as “big data.” Andwiththisfloodofdatacomesatidalwaveofopportunity.Researchhasfoundthatcompanies ranked in the top third of their industry in the use of data-driven decision making were on average 5 percent more productive and 6 percent more profitable than competitors.[4]Increasingly standardized corporate data, and access to rich, third-party data sets—all leveraged by cheap, fast computing and easier-to-usesoftware—arecollectivelyenablinganewageofdata-driven,fact-baseddecisionmaking. You’relesslikelytohearold-schooltermslike“decisionsupportsystems”usedtodescribewhat’sgoing onhere.Thephraseofthedayisbusinessintelligence(BI),acatchalltermcombiningaspectsofreporting, data exploration and ad hoc queries, and sophisticated data modeling and analysis.
- Alongside business intelligence in the new managerial lexicon is the phrase analytics, a term describing the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and factbased management to drive decisions and actions (and in our ever-imprecise world of business buzzwords,you’lloftenhearbusinessintelligenceandanalyticsusedinterchangeablytomeanthesame thing—usingdataforbetterdecisionmaking).[5] Anothertrend,machinelearning,referstoasophisticated category of software applications known as artificial intelligence that leverage massive amountsofdatasothatcomputerscan“learn”andimprovetheaccuracyofactionsandpredictionson their own without additional programming.[6] The benefits of all this data and number crunching are very real, indeed. Data leverage lies at the center of competitive advantage in many of the firms that we’ve studied, including Amazon, Netflix and Zara. Data mastery has helped vault Walmart to the top of the Fortune 500 list. It helps Spotify craft you a killer playlist for your run. And it helps make Google’s voice recognition a better listener andGooglesearchabetterdetective,sothattheservicecanaccuratelyshowyouwhatyou’veaskeditto lookup.There’sevensomethinghereforPoliScimajors,sincedata-driveninsightsareincreasinglybeing credited with helping politicians win elections.[7] To quote from a BusinessWeek cover story on analytics, “Math Will Rock Your World!”[8] Soundsgreat,butitcanbeatoughsloggettinganorganizationtothepointwhereithasaleveragable data asset. In many organizations data lies dormant, spread across inconsistent formats and incompatible systems, unable to be turned into anything of value. Many firms have been shocked at the amount of work and complexity required to pull together an infrastructure that empowers its managers.Butnotonlycanthisbedone,itmustbedone.Firmsthatarebasingdecisionsonhunchesaren’t managing, they’re gambling. And today’s markets have no tolerance for uninformed managerial dice rolling. Whilewe’llstudytechnologyinthischapter,ourfocusisn’tasmuchonthetechnologyitselfasitis onwhatyoucandowiththattechnology.ConsumerproductsgiantP&Gbelievesinthisdistinctionso thoroughlythatthefirmrenameditsITfunctionas“InformationandDecisionSolutions.”[9]Solutions drive technology decisions, not the other way around. Inthischapterwe’llstudythedataasset,howit’screated,howit’sstored,andhowit’saccessedand leveraged.We’llalsostudymanyofthefirmsmentionedabove,andmore,providingacontextforunderstanding how managers are leveraging data to create winning models, and how those that have failed to realize the power of data have been left in the dust.
- Data, Analytics, and Competitive Advantage Anyone can acquire technology—but data is oftentimes considered a defensible source of competitive advantage. The data a firm can leverage is a true strategic asset when it’s rare, valuable, imperfectly imitable, and lacking in substitutes (seeChapter 2). If more data brings more accurate modeling, moving early to capture this rare asset can be the difference between a dominating firm and an also-ran. But be forewarned, there’s no monopoly on math. Advantages based on formulas, algorithms, and data that others can also acquire will be short-lived. Moneyball advances in sports analytics originally pioneered by the Oakland A’s and are now used by nearly every team in the major leagues. This doesn’t mean that firms can ignore the importance data can play in lowering costs, increasing customer service, and other ways that boost performance. But differentiation will be key in distinguishing operationally effective data use from those efforts that can yield true strategic positioning.
- That Seat Will Cost You $8−Wait, Make That $45.50 For some games it’s tough to fill the stands. A Wednesday night game against a mediocre rival will prompt thousands to stay home unless they get a really compelling deal. But many fans are ready to pay big bucks for a rivalry game on a weekend. To optimize demand, over thirty teams in Major League Baseball (MLB), the National Basketball Association (NBA), National Hockey League (NHL), and Major League Soccer (MLS) are using data analytics from Austin-based Qcue to fill seats and maximize revenue.[10] Take the San Francisco Giants as an example. The baseball standout draws big crowds when playing crosstown, interleague rivals, the Oakland As. A seat in the left field, upper deck of AT&T Park will cost above $45 for a Saturday afternoon game. But when the Diamondbacks are in town on a work or school night, that verysameseatcanbehadfor$8.Changingpricingbasedondemandconditionsisknownasdynamicpricing, and the Giants credits analytics-driven demand pricing with helping bump ticket revenues by at least 6 percent in a single year[11]and fuel a 250-plus sellout streak.[12]And getting fans in the stands is critical since once there, those fans usually rack up even more revenue in the form of concessions and merchandise sales. Dynamic pricing can be tricky. In some cases, it can leave consumers feeling taken advantage of (it is especially tricky in situations where consumers make repeated purchases and are more likely to remember past prices, and when they have alternative choices, like grocery or department store shopping). But dynamic pricing often works in markets where supply is constrained and subject to demand spikes. Firms from old-school airlines toapp-savvyUberregularlyletdataanalyticssetasupply-demandequilibriumthroughdynamicpricing,while also helping boost their bottom line. Sports teams are even leveraging weather insights and other data to drive the pricing of concession specials and to set the cost of a beer. New technologies, such as iBeacon (a tech that sends messages to iPhones using a low-energy Bluetooth signal) are being rolled out throughout MLB, making it easier to let consumers know a deal is in effect and guiding them to the quickest counter for quenching thirst and satisfying cravings.[13] FIGURE 15.1 Major League Baseball’s At the Ballpark app will use iBeacon technology to distribute deals and guide you to concessions. Source: Alex Colon, “MLB Completes iBeacon Installations at Dodger Stadium and Petco Park,” GigaOM, February 14, 2014, https://gigaom.com/2014/02/14/mlb-completes-ibeacon-installations-at-dodger-stadium-and-petco-park.
- KEY TAKEAWAYS < The amount of data being created doubles every two years. < In many organizations, available data is not exploited to advantage. However new tools supportingbig data, business intelligence, and analytics are helping managers make sense of this data torrent. < Data is oftentimes considered a defensible source of competitive advantage; however, advantages based on capabilities and data that others can acquire will be short-lived.
- 1. Name and define the terms that are supplanting discussions of decision support systems in the modern IS lexicon.
- 2. Is data a source of competitive advantage? Describe situations in which data might be a source for sustainable competitive advantage. When might data not yield sustainable advantage?
- 3. Are advantages based on analytics and modeling potentially sustainable? Why or why not?
- 4. Think about the amount of data that is collected about you every day. Make a list of various technologies and information systems you engage with and the organizations that use these technologies, systems, and services to learn more about you. Does this information serve you better as a consumer? What, if any, concerns does broad data collection leave you with?
- 5. What role do technology and timing play in realizing advantages from the data asset?
- 6. What do you think about dynamic pricing? Is it good or bad for consumers? Is it good or bad for businesses? Explain your answer.
- 7. Have you visited a retailer or other venue using iBeacons? If so, describe your experience. If not, research the technology and come to class prepared to discuss its implications for collecting data and for driving consumer actions.