Bijna 70% van de bedrijven mist de “big data” trein

Jonas
Vandenbruaene

Big data is hot. Uit thesisonderzoek van Jonas Vandenbruaene blijkt dat ook bedrijven massaal op zoek gaan naar toepassingen. Echter, de implementatie van de technologie die nodig is om grote hoeveelheden informatie te analyseren verloopt vaak moeizaam. Hierdoor slaagt slechts 30% van de organisaties erin de hype te valoriseren.

I’ll be back”. Met deze woorden uit de ‘The Terminator’ maakte Arnold Schwarzenegger zich meer dan onsterfelijk. De film uit 1984 gaat (#spoileralert) over slimme computerprogramma’s (artificiële intelligentie) die op eigen houtje een kernoorlog starten. De visuele effecten mogen dan wel archeologisch aanvoelen, de film geeft een mooi inzicht in hoe Jan Modaal vroeger over artificiële intelligentie dacht: als iets onbegrijpelijks, duister en vooral bijzonder gevaarlijk.

Van opgepast naar toegepast

Deze Hollywood-definitie van artificiële intelligentie werd de laatste decennia beetje bij beetje onder de mat geveegd. Door de grote vooruitgang binnen het domein zijn we collectief anders over artificiële intelligentie gaan denken: van een mysterieuze, bedreigende entiteit naar een handig, alledaags gebruiksvoorwerp. Een zakrekenmachine voor gevorderden. De soms vergezochte sci-fi’s werden in sneltempo vervangen door een stortvloed aan artikels waarin de praktische toepassingen van artificiële intelligentie uiteengezet werden. Geniale schaakcomputers, chatbots, zelfrijdende auto’s of verbeterde kankerdiagnoses, de mogelijkheden lijken eindeloos.

Surfen op de data-tsunami

In het eerste deel van het onderzoek wordt gepeild naar de interesse van bedrijfsleiders in analytics: de dataverwerking. Deze tak van de artificiële intelligentie is relevanter dan ooit doordat steeds meer mensen vergroeid raken met hun laptop of smartphone. Hierdoor worden er meer data gecreëerd dan ooit tevoren. Om je een idee te geven: elke dag worden er zo’n 205 miljard (!) e-mails verstuurd en wordt er zo’n 400.000 uur aan Youtube-video’s geüpload.  Deze data-tsunami, soms ook wel big data genoemd, is een goudmijn voor bedrijven die weten hoe ze ermee om moeten gaan.

Uit het thesisonderzoek blijkt dat meer dan 70% van de bedrijven analytics als zeer of extreem belangrijk beschouwd. Verder merken we dat organisaties analytics willen inzetten om een opmerkelijk breed spectrum van doelen te bereiken: van het beter begrijpen van de klant tot het verhogen van de omzet. (En om de  paranoïde lezer gerust te stellen, het uitroeien van de mensheid werd door geen van de onderzochte bedrijven vermeld als doel.) Echter, slechts de helft van alle analytics-gerelateerde ambities die organisaties hebben, wordt gerealiseerd. Dit brengt ons bij het tweede deel van de thesis, namelijk hoe bedrijfsleiders ervoor kunnen zorgen dat de implementatie van analytics in hun firma succesvol verloopt. Wat moet de CEO van een Vlaams familiebedrijfje doen om zijn firma om te bouwen van een Volkswagen Kever naar een blitse Tesla? Oftewel, hoe kan deze CEO de maturiteit van zijn bedrijf met betrekking tot analytics verhogen.

Een rups leren vliegen

Bedrijfswetenschappers bestuderen de implementatie van nieuwe technologieën in organisaties typisch door gebruik te maken van maturiteitsmodellen. Dit zijn patronen die beschrijven hoe bedrijven veranderen doorheen de tijd. Het is een landkaart die laat zien welk pad er gevolgd wordt voordat een organisatie iets volledig onder de knie heeft. Dit klinkt zeer abstract, laat ik er een voorbeeld bijhalen. Elke vlinder wordt geboren uit een ei. Na verloop van tijd komt er een rups uit het ei. Die rups kruipt in een tentje: de pop, waaruit later een prachtige vlinder tevoorschijn komt. Voilà, een maturiteitsmodel met vier fases.

Zo bestaan er ook in het domein van de analytics verschillende maturiteitsmodellen die beschrijven hoe een bedrijf volwassen wordt. Wat de meeste van deze modellen gemeen hebben is dat ze opgesteld worden door deductie. Dit wil zeggen dat een wetenschapper vanuit bepaalde theoretische aannames een model fabriceert. Deze modellen zijn heel mooi op papier, maar het is niet volledig duidelijk of ze er ook in slagen om de realiteit op een waarheidsgetrouwe manier te beschrijven. En laat dit nu net het doel van de wetenschap zijn!

Bedrijven zijn geen vlinders

Om te begrijpen hoe bedrijven transformeren, is het een goed idee om te werken met inductieve maturiteitsmodellen. Dit zijn modellen die opgebouwd zijn uit het veralgemenen van zeer veel observaties. In plaats van te starten vanuit een theorie kijken we naar hoe het er in de praktijk aan toegaat. Het hoofdgerecht van deze thesis is een nieuw, inductief maturiteitsmodel. Dit werd ontwikkeld door alle data die verzameld werden tijdens de marktstudie samen te voegen en ze te verwerken met een algoritme (een soort computerprogramma). Wat blijkt nu? Bedrijven zijn geen vlinders: groei verloopt vaak niet rechtlijnig. Veel maturiteitsmodellen stellen transformaties voor als eenrichtingsverkeer: een pop wordt een vlinder, en nooit andersom. Als we naar de realiteit kijken zien we dat dit soort terugval weldegelijk voorkomt.

Hierna kunnen we het model gebruiken om te kijken in welke fases bedrijven zich op dit moment bevinden. Welk percentage van de vlinders zitten er nog in een ei, hoeveel rupsen zijn er al, dit soort uitspraken. Na deze analyse merken we dat bijna 70% van de organisaties zich nog op een zeer laag maturiteitsniveau bevinden met betrekking tot big data en analytics. Voor deze groep is het zeer belangrijk om snel na te denken over hoe ook zij de vruchten van analytics kunnen plukken, willen ze op de lange termijn overleven. Het opgestelde maturiteitsmodel kan een wegenkaart zijn voor de bedrijven die hun maturiteit met betrekking tot analytics willen verhogen.  

Conclusie

Wat kunnen we uit deze onderzoeksresultaten leren? Ten eerste is de interesse in big data en analytics zeer groot, maar er is nog veel werk aan de winkel. Ten tweede is het voor bedrijfsleiders belangrijk om in te zien dat de ontwikkeling van een bedrijf zeker niet altijd rechtlijnig gebeurt. Ten derde is het voor onderzoekers interessant om te onthouden dat patronen die in theorie goed klinken vaak niet in de realiteit weerspiegeld worden.

En om af te sluiten, hoeveel Terminator-films zullen er gemaakt zijn voordat artificiële intelligentie een bedreiging vormt voor de mensheid? Moeilijk te voorspellen, maar wees maar zeker: they’ll be back.

 

 

Bibliografie

Accenture,. (2014). Big Success With Big Data. Retrieved from https://www.accenture.com/ie- en/_acnmedia/Accenture/Conversion-Assets/DotCom/Documents/Global/PDF/Industries_14/Accenture-Big- Data-POV .pdf

Accenture,. (2016). Analytics Everywhere Smarter Actions, Happier Customers, Greater Value. Retrieved from https://www.accenture.com/us-en/~/media/PDF-26/Accenture-CMT-Analytics-…

Accenture. (2010). Counting on Analytical Talent. Retrieved from http://www.criticaleye.com/insights- servfile.cfm?id=2125&view=1

Achenwall, Gottfried. (2012). Infoplease.com. Retrieved 30 December 2016, from http://www.infoplease.com/encyclopedia/people/achenwall-gottfried.html

Ackoff, R. (1989). From data to wisdom. Journal Of Applied Systems Analysis, 16, 3-9.

Agarwal, G. (2015). 5 Megatrends Driving the Chief Analytics Officer Role. GoodData. Retrieved 21 March

2017, from https://www.gooddata.com/blog/5-megatrends-driving-chief-analytics-offi…

Ament, P. (2006). Abacus History - Invention of the Abacus. Ideafinder.com. Retrieved 28 February 2017, from http://www.ideafinder.com/history/inventions/abacus.htm

Analysis. (2016). Oxford Dictionary. Retrieved from https://en.oxforddictionaries.com/definition/analysis

Analytics. (2016). Oxford Dictionary. Retrieved from https://en.oxforddictionaries.com/definition/analytics

Andrews, K. (1980). The concept of corporate strategy (1st ed.). R. D. Irwin, Homewood, Ill.

Armstrong, J. & Overton, T. (1977). Estimating Nonresponse Bias in Mail Surveys. Journal Of Marketing Research, 14(3), 396. http://dx.doi.org/10.2307/3150783

Arts, J. (2016). Antwerpen.

AT Kearny,. (2013). Big Data and the Creative Destruction of Today’s Business Models. Retrieved from https://www.atkearney.com/documents/10192/698536/Big+Data+and+the+Creat… usiness+Models.pdf/f05aed38-6c26-431d-8500-d75a2c384919

Augur, H. (2016). Can Big Data Save Your Love Life? Online Dating Apps Say “Yes” - Dataconomy. Dataconomy. Retrieved 11 April 2017, from http://dataconomy.com/2016/02/can-big-data-save-your-love-life/

Baesens, B. (2014). Analytics in a big data world (1st ed.). Hoboken (N.J.): J. Wiley & Sons. Bain. (2013). Big Data: The organizational challenge. Retrieved from

http://www.bain.com/Images/BAIN_BRIEF_Big_Data_The_organizational_chall…

Bean, R. (2016). Big Data And The Emergence Of The Chief Data Officer. Forbes.com. Retrieved 13 March 2017, from https://www.forbes.com/sites/ciocentral/2016/08/08/big-data-and-the-eme…- officer/#571819bbba94

Beck, A., Sangoi, A., Leung, S., Marinelli, R., Nielsen, T., & van de Vijver, M. et al. (2011). Systematic Analysis of Breast Cancer Morphology Uncovers Stromal Features Associated with Survival. Science Translational Medicine, 3(108), 108ra113-108ra113. http://dx.doi.org/10.1126/scitranslmed.3002564

Becker, J. (2010). Maturity Models in IS Research. ECIS 2010 Proceedings, 42. Retrieved from http://aisel.aisnet.org/ecis2010/42/

Becker, J., Knackstedt, R., & Pöppelbuß, J. (2009). Developing Maturity Models for IT Management. Business & Information Systems Engineering, 1(3), 213-222. http://dx.doi.org/10.1007/s12599-009-0044-5

Becker, J., Niehaves, B., Poeppelbuss, J., & Simons, A. (2010). Maturity Models in IS Research. ECIS 2010 Proceedings, 42. Retrieved from http://aisel.aisnet.org/ecis2010/42

Beyond Moore's law. (2015). The Economist. Retrieved 6 February 2017, from http://www.economist.com/news/science-and-technology/21652051-even-afte…- could-still-halve-every-few-years-beyond

Biehn, N. The Missing V’s in Big Data: Viability and Value. Wired. Retrieved 14 December 2016, from https://www.wired.com/insights/2013/05/the-missing-vs-in-big-data-viabi…

Bien, F. (2014). It’s Time To Welcome The Chief Analytics Officer To The C-suite | Fast Company. Fast Company. Retrieved 21 March 2017, from https://www.fastcompany.com/3033590/the-future-of-work/its-time- to-welcome-the-chief-analytics-officer-to-the-c-suite

Box, G. (1976). Science and Statistics. Journal Of The American Statistical Association, 71(356), 791-799. http://dx.doi.org/10.1080/01621459.1976.10480949

Bradshaw, J. Why k-modes. Daylight.com. Retrieved 8 April 2017, from http://www.daylight.com/meetings/mug04/Bradshaw/why_k-modes.html

Brynjolfsson, E., Hitt, L., & Kim, H. (2011). Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance?. SSRN Electronic Journal. http://dx.doi.org/10.2139/ssrn.1819486

Bulygo, Z. (2013). How Netflix Uses Analytics To Select Movies, Create Content, & Make Multimillion Dollar Decisions. Retrieved 5 March 2017, from https://blog.kissmetrics.com/how-netflix-uses-analytics/

Buringh, E. & Van Zanden, J. (2009). Charting the “Rise of the West”: Manuscripts and Printed Books in Europe, A Long-Term Perspective from the Sixth through Eighteenth Centuries. The Journal Of Economic History, 69(02), 417. http://dx.doi.org/10.1017/s0022050709000837

Burnton, S. (2012). 50 stunning Olympic moments No28: Dick Fosbury introduces 'the flop'. the Guardian. Retrieved 28 February 2017, from https://www.theguardian.com/sport/blog/2012/may/08/50-stunning-olympic- moments-dick-fosbury

Burtchell, M. (2016). The Rise of The Chief Digital Officer: Why You Need One and What to Look For. Salsify.com. Retrieved 8 March 2017, from http://www.salsify.com/blog/the-rise-of-the-chief-digital-officer- why-you-need-one-and-what-to-look-for

CA Technologies,. (2015). The State of Big Data Infrastructure: Benchmarking global Big Data users to drive future performance. Retrieved from https://www.ca.com/content/dam/ca/us/files/industry-analyst-report/the- state-of-big-data-infrastructure.pdf

Capgemini Consulting,. (2014). Cracking the Data Conundrum: How Successful Companies Make Big Data Operational. Retrieved from https://www.capgemini-consulting.com/resource-file- access/resource/pdf/cracking_the_data_conundrum-big_data_pov_13-1-15_v2.pdf

Carifio, J., & Perla, R. (2007). Ten Common Misunderstandings, Misconceptions, Persistent Myths and Urban Legends about Likert Scales and Likert Response Formats and their Antidotes. Journal Of Social Sciences, 3(3), 106-116. http://dx.doi.org/10.3844/jssp.2007.106.116

Caudron, J., & Peteghem, D. (2015). Digital transformation (1st ed.). Duval Union Consulting.

Cavanillas, J., Curry, E., & Wahlster, W. (2016). New horizons for a data-driven economy: a roadmap for usage

and exploitation of big data in Europe. Springer Open. http://dx.doi.org/10.1007/s40558-016-0061-4

Choo, C. (1996). The knowing organization: How organizations use information to construct meaning, create knowledge and make decisions. International Journal Of Information Management, 16(5), 329-340. http://dx.doi.org/10.1016/0268-4012(96)00020-5

Cleveland, H. (1985). The knowledge executive (1st ed.). New York: Truman Talley Books.

Conneally, T. (2013). 'Chief Digital Officer' is the next hot executive title, says Gartner. BetaNews. Retrieved 8 March 2017, from https://betanews.com/2012/10/22/chief-digital-officer-is-the-next-hot-e…- gartner/

Cosic, R., Shanks, G., & Maynard, S. (2012). Towards a Business Analytics Capability Maturity Model. Retrieved from https://pdfs.semanticscholar.org/7ff9/78d5dd970101c681383fcb168b49efee6…

Cost of Computing Power Equal to an iPad2 | The Hamilton Project. (2011). Hamiltonproject.org. Retrieved 6 February 2017, from http://www.hamiltonproject.org/charts/cost_of_computing_power_equal_to_…

Costagliola, G., Fuccella, V., Giordano, M., & Polese, G. (2009). Monitoring Online Tests through Data Visualization. IEEE Transactions On Knowledge And Data Engineering, 21(6), 773-784. http://dx.doi.org/10.1109/tkde.2008.133

Coutuer, J. (2017). Data & Analytics maturity interview. Brussels.

Dartmouth, U. (2016). Master of Science - UMass Dartmouth. Umassd.edu. Retrieved 31 December 2016, from http://www.umassd.edu/datascience/masterofscience/

Data. (2016). Oxford Dictionary. Retrieved from https://en.oxforddictionaries.com/definition/data

DataFlux,. (2007). The Data Governance Maturity Model Establishing the People, Policies and Technology That Manage Enterprise Data. Retrieved from http://www.fstech.co.uk/fst/whitepapers/The_Data_Governance_Maturity_Mo…

Davenport, T. (2013). Enterprise analytics (1st ed.). Upper Saddle River, N.J.: FT Press.

Davenport, T. & Patil, D. (2012). Data Scientist: The Sexiest Job of the 21st Century. Harvard Business Review.

Retrieved 29 December 2016, from https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-cent…

Davenport, T. & Prusak, L. (2000). Working knowledge (1st ed.). Boston, Mass.: Harvard Business School Press.

Davenport, T., & Dallemule, L. (2017). What’s Your Data Strategy?. Harvard Business Review, (May-June), 112-121. Retrieved from https://hbr.org/2017/05/whats-your-data-strategy

Davenport, T., & Harris, J. (2007). Competing on analytics (1st ed.). Boston (Mass.): Harvard Business School Press.

Davenport, T., Harris, J., & Morison, R. (2010). Analytics at work (1st ed.). Boston, Mass: Harvard Business Press.

Davidian, M. & Louis, T. (2012). Why statistics?. Science, 336. Retrieved from https://www.stat.wisc.edu/~wahba/science.whystat.pdf

Davis, G. & Olson, M. (1985). Management information systems (1st ed.). New York: McGraw-Hill.

de Brí, F. (2009). An e-Government Stages of Growth Model Based on Research Within the Irish Revenue

Offices. Electronic Journal Of E-Government, 7(4), 339 - 348.

Deloitte,. (2015). The rise of the Chief Digital Officer. Retrieved from http://www.deloittedigital.ca/chief-

digital-officer

Deloitte,. (2016). The evolving role of the chief data officer in financial services. Retrieved from https://www2.deloitte.com/content/dam/Deloitte/uy/Documents/strategy/gx…- officer.pdf

DeLucia, N. (2016). The History of Printing. Inksterinc. Retrieved 30 December 2016, from http://www.inksterprints.com/inksterprints-blog/the-history-of-printing

Descriptive, Predictive, and Prescriptive Analytics Explained. (2016). Halo. Retrieved 31 December 2016, from https://halobi.com/2016/07/descriptive-predictive-and-prescriptive-anal…

Deseure, A. (2017). Data & Analytics maturity. Antwerpen.

Devens, R. (1865). Cyclopaedia of commercial and business anecdotes (1st ed.). New York: D. Appleton and Company.

Donnelly, C., & Simmons, G. (2013). Small Businesses Need Big Data, Too. Harvard Business Review. Retrieved 17 March 2017, from https://hbr.org/2013/12/small-businesses-need-big-data-too

Douglas, T. (2016). The rise and fall of big data hype—and what it means for customer intelligence. Vision Critical. Retrieved 29 December 2016, from https://www.visioncritical.com/fall-of-big-data-hype/

Drexler, K. (2013). Radical abundance: How a Revolution in Nanotechnology Will Change Civilization (1st ed.). PublicAffairs,U.S.

Driscoll, M. (2012). Michael E. Driscoll on Twitter. Twitter. Retrieved 15 January 2017, from https://twitter.com/medriscoll/status/225333351526051842?ref_src=twsrc%…

Drucker, P. (2008). Classic drucker (1st ed.). Boston: Harvard Business Press.

EY & Forbes Insights,. (2015). Analytics: don't forget the human element. Retrieved from http://www.ey.com/Publication/vwLUAssets/EY -Forbes-Insights-Data-and-Analytics-Impact-Index- 2015/$FILE/EY -Forbes-Insights-Data-and-Analytics-Impact-Index-2015.pdf

Fallows, J. (2013). The 50 Greatest Breakthroughs Since the Wheel. The Atlantic. Retrieved 28 February 2017, from https://www.theatlantic.com/magazine/archive/2013/11/innovations-list/3…

Finnemann, N. (2001). The Internet – A New Communicational Infrastructure (1st ed.). Skrifter fra Center for Internetforskning. Retrieved from http://web.archive.org/web/20040328165322/http://cfi.imv.au.dk/pub/skri…

Foo, A. (2013). The Emerging Role of the Chief Analytics Officer. IBM Big Data & Analytics Hub. Retrieved 21 March 2017, from http://www.ibmbigdatahub.com/blog/emerging-role-chief-analytics-officer

Forrester,. (2015). Top Performers Appoint Chief Data Officers. Retrieved from https://www.forrester.com/report/Top+Performers+Appoint+Chief+Data+Offi…

Forrester,. (2016). The Digital Maturity Model 4.0. Retrieved from https://www.forrester.com/report/The+Digital+Maturity+Model+40/-/E-RES1…

Fraser, P., Moultrie, J., & Gregory, M. (2002). The use of maturity models / grids as a tool in assessing product development capability: a review. IEEE International Engineering Management Conference. Retrieved from http://www.academia.edu/3391259/The_use_of_maturity_models_grids_as_a_t… opment_capability

Gambill, M. (2016). What Is A Chief Data Officer And Why Do Firms Need Them?. Forbes.com. Retrieved 13 March 2017, from https://www.forbes.com/sites/kimberlywhitler/2016/10/22/what-is-a-chief…- why-do-firms-need-them/#5de1e61bc94a

Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal Of Information Management, 35(2), 137-144. http://dx.doi.org/10.1016/j.ijinfomgt.2014.10.007 Gartner,. (2012). Gartner Says Every Budget is Becoming an IT Budget. Gartner.com. Retrieved 8 March 2017, from http://www.gartner.com/newsroom/id/2208015

Gartner,. (2016). Gartner CDO Survey Reveals That Chief Data Officers Drive Both Data Management and Analytics for Maximum Impact. Retrieved from https://www.gartner.com/doc/3514317

Gartner,. (2016). Gartner Estimates That 90 Percent of Large Organizations Will Have a Chief Data Officer by 2019. Gartner.com. Retrieved 14 March 2017, from http://www.gartner.com/newsroom/id/3190117

Gartner,. (2017). Hype Cycle Research Methodology | Gartner Inc.. Gartner.com. Retrieved 13 April 2017, from http://www.gartner.com/technology/research/methodologies/hype-cycle.jsp

Gartner's analytic value escalator. (2016). Flickr. Retrieved 31 December 2016, from https://www.flickr.com/photos/27772229@N07/8267855748/in/photostream

Ghahramani, Z. (2015). Data Science and Statistics: different worlds?. YouTube. Retrieved 15 January 2017, from https://www.youtube.com/watch?v=C1zMUjHOLr4

Ghosh, S., Little, R., & Rubin, D. (1988). Statistical Analysis with Missing Data. Technometrics, 30(4), 455. http://dx.doi.org/10.2307/1269814

Gibson, C. & Nolan, R. (1974). Managing the Four Stages of EDP Growth. Harvard Business Review. Retrieved from https://hbr.org/1974/01/managing-the-four-stages-of-edp-growth

Granville, V. (2015). Data Scientist vs Statistician. Datasciencecentral.com. Retrieved 2 January 2017, from http://www.datasciencecentral.com/profiles/blogs/data-scientist-vs-stat…

Green, S. (2011). Business Jargon Is Not a “Value-Add”. Harvard Business Review. Retrieved 28 February 2017, from https://hbr.org/2011/12/business-jargon-is-not-a-value

Grimes, S. (2013). Big Data: Avoid 'Wanna V' Confusion - InformationWeek. InformationWeek. Retrieved 14 December 2016, from http://www.informationweek.com/big-data/big-data-analytics/big-data-avo…- confusion/d/d-id/1111077?page_number=1

Guess, A. (2015). Only 0.5% of All Data is Currently Analyzed - DATAVERSITY. DATAVERSITY. Retrieved 7 February 2017, from http://www.dataversity.net/only-0-5-of-all-data-is-currently-analyzed/

Gung,. (2015). How to use both binary and continuous variables together in clustering?. Stats.stackexchange.com. Retrieved 8 April 2017, from http://stats.stackexchange.com/questions/130974/how- to-use-both-binary-and-continuous-variables-together-in-clustering

Halevi, G. & Moed, H. (2012). The Evolution of Big Data as a Research and Scientific Topic (1st ed.). Research Trends. Retrieved from https://www.researchtrends.com/wpcontent/uploads/2012/09/Research_Trend…

Hamers, B. (2017). Data & Analytics maturity. Brussels. Harari, Y. (2011). Sapiens (1st ed.). Vintage Books.

Harris, J. (2016). History of Storage from Cave Paintings to Electrons (Infographic) - Remo Software - Info. Remo Software - Info. Retrieved 17 January 2017, from http://www.remosoftware.com/info/history-of-storage- from-cave-paintings-to-electrons

Hartshorne, C. & Weiss, P. (1934). Collected Papers of Charles Sanders Peirce. The Journal Of Philosophy, 31(21), 582. http://dx.doi.org/10.2307/2015395

Henry, N. (1974). Knowledge Management: A New Concern for Public Administration. Public Administration Review, 34(3). http://dx.doi.org/10.2307/974902

Herbsleb, J., Zubrow, D., Goldenson, D., Hayes, W., & Paulk, M. (1997). Software quality and the Capability Maturity Model. Communications Of The ACM, 40(6), 30-40. http://dx.doi.org/10.1145/255656.255692

Hortonworks,. (2016). Big data maturity model. Retrieved from http://hortonworks.com/wp- content/uploads/2016/04/Hortonworks-Big-Data-Maturity-Assessment.pdf

Huang, Z. (1998). Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values. Data Mining And Knowledge Discovery, 2, 283-304. Retrieved from http://www.cs.ust.hk/~qyang/Teaching/537/Papers/huang98extensions.pdf

IBM - What is big data?. (2012). Retrieved 30 January 2017, from https://www- 01.ibm.com/software/data/bigdata/what-is-big-data.html

IBM,. (2007). Data Governance Council Maturity Model. Retrieved from https://www- 935.ibm.com/services/uk/cio/pdf/leverage_wp_data_gov_council_maturity_model.pdf

IBM,. (2016). IBM Clustering binary data with K-Means (should be avoided) - United States. Www- 01.ibm.com. Retrieved 8 April 2017, from http://www-01.ibm.com/support/docview.wss?uid=swg21477401

IBM. (2014). The new hero of big data and analytics. Retrieved from http://www- 07.ibm.com/au/pdf/GBE03607USEN9.pdf

Ifrah, G. (2001). The universal history of computing (1st ed.). New York: John Wiley.

Information. (2003). Merriam-Webster. Retrieved from https://www.merriam- webster.com/dictionary/information

Information. (2016). Oxford Dictionary. Retrieved from https://en.oxforddictionaries.com/definition/information

Inmon, W. (2016). Data lake architecture (1st ed.). Basking Ridge, NJ: Technics Publications.

Iversen, J., Nielsen, P., & Norbjerg, J. (1999). Situated assessment of problems in software development. ACM

SIGMIS Database, 30(2), 66-81. http://dx.doi.org/10.1145/383371.383376

Jayaraman, S. (2012). Enabling Strategic Decision Making: The role of Decision Support Systems in banks |

Fintellix Blog. Fintellix.com. Retrieved 4 April 2017, from http://www.fintellix.com/blog/?p=117

Johnston, C. (2016). The Rise of the Chief Digital Officer - Disruption. Disruption. Retrieved 8 March 2017,

Jones, G. (2010). Organizational theory, design, and change (1st ed.). Upper Saddle River, N.J.: Pearson.

Khan, S. (2016). Can we use K-means for clustering binary vectors?. Quora. Retrieved 8 April 2017, from https://www.quora.com/Can-we-use-K-means-for-clustering-binary-vectors

Knowledge. (2016). Oxford Dictionary. Retrieved from https://en.oxforddictionaries.com/definition/knowledge

Knudson, K. (2016). Use Your Fingers: The Abacus Just Might Improve Your Arithmetic Abilities. Forbes.com. Retrieved 29 December 2016, from http://www.forbes.com/sites/kevinknudson/2016/04/28/use-your-fingers- the-abacus-just-might-improve-your-arithmetic-abilities/#4d54a989590d

Kohlschütter, C. (2011). How much data is "Big Data"?. Quora. Retrieved 14 December 2016, from https://www.quora.com/How-much-data-is-Big-Data

Kopalle, P. (2014). Why Amazon's Anticipatory Shipping Is Pure Genius. Forbes.com. Retrieved 5 March 2017, from https://www.forbes.com/sites/onmarketing/2014/01/28/why-amazons-anticip…- genius/#744fee184605

Kowalke, P. (2016). Six Ways to Use Big Data If Your Company is Small. It.toolbox.com. Retrieved 18 March 2017, from http://it.toolbox.com/blogs/inside-erp/six-ways-to-use-big-data-if-your…

KPMG,. (2016). Building trust in analytics. Retrieved from https://assets.kpmg.com/content/dam/kpmg/xx/pdf/2016/10/building-trust-…

KPMG,. Effective master data management. Retrieved from https://www.compact.nl/articles/effective-master- data-management/#Maturity_model_for_master_data_management

Lahrmann, G., Marx, F., Winter, R., & Wortmann, F. (2011). Business Intelligence Maturity: Development and Evaluation of a Theoretical Model. Proceedings Of The 44Th Hawaii International Conference On System Sciences. http://dx.doi.org/DOI: 10.1109/HICSS.2011.90

Laney, D. (2001). 3D data management: Controlling data volume, velocity, and variety. Technical Report, META Group. Retrieved from https://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Manage…- Controlling-Data-Volume-Velocity-and-Variety.pdf

Laney, D. (2013). Batman on Big Data - Doug Laney. Gartner. Retrieved 14 December 2016, from http://blogs.gartner.com/doug-laney/batman-on-big-data/

Leaper, B. (2014). The Rise of the Chief Data Officer. WIRED. Retrieved 13 March 2017, from https://www.wired.com/insights/2014/07/rise-chief-data-officer/

Lee, J., Jones, P., Mineyama, Y., & Zhang, X. (2002). Cultural differences in responses to a likert scale. Research In Nursing & Health, 25(4), 295-306. http://dx.doi.org/10.1002/nur.10041

Lewis, M. (2003). Moneyball (1st ed.). New York: W.W. Norton.

Lismont, J., Vanthienen, J., Baesens, B., & Lemahieu, W. (2017). Defining analytics maturity indicators: A survey approach. International Journal Of Information Management, 37(3), 114-124. http://dx.doi.org/10.1016/j.ijinfomgt.2016.12.003

Marr, B. (2015). Big Data: 20 Mind-Boggling Facts Everyone Must Read. Forbes.com. Retrieved 6 February 2017, from http://www.forbes.com/sites/bernardmarr/2015/09/30/big-data-20-mind-bog…- must-read/#4724296d6c1d

Marr, B. (2015). Big Data: Using SMART Big Data; Analytics and Metrics To Make Better Decisions and Improve Performance (1st ed.). Wiley.

Marr, B. (2015). How small businesses can get started with big data. Hiscox Business Blog. Retrieved 18 March 2017, from https://www.hiscox.co.uk/business-blog/bernard-marr-column-small-busine…- data/

Martens, D. (2017). Methodological question thesis.

Maturity. (2010). Webster’s New World College Dictionary. Retrieved from http://www.yourdictionary.com/maturity#websters

Mazzei, M. & Noble, D. (2017). Big data dreams: A framework for corporate strategy. Business Horizons. http://dx.doi.org/10.1016/j.bushor.2017.01.010

McAfee, A. (2013). Big Data’s Biggest Challenge? Convincing People NOT to Trust Their Judgment. Harvard Business Review. Retrieved 4 April 2017, from https://hbr.org/2013/12/big-datas-biggest-challenge-convincing- people-not-to-trust-their-judgment

McCall, T. (2015). Understanding the Chief Data Officer (CDO) Role - Smarter With Gartner. Smarter With Gartner. Retrieved 11 March 2017, from http://www.gartner.com/smarterwithgartner/understanding-the-chief- data-officer-role/

McElheran, K., & Brynjolfsson, E. (2016). The Rise of Data-Driven Decision Making Is Real but Uneven. Harvard Business Review. Retrieved 4 April 2017, from https://hbr.org/2016/02/the-rise-of-data-driven- decision-making-is-real-but-uneven

McKinsey,. (2013). Game changers: Five opportunities for US growth and renewal. Retrieved 21 March 2017, from http://www.mckinsey.com/global-themes/americas/us-game-changers

McKinsey,. (2013). Mobilizing your C-suite for big-data analytics. McKinsey & Company. Retrieved 21 March 2017, from http://www.mckinsey.com/business-functions/digital-mckinsey/our-insight…- suite-for-big-data-analytics

McKinsey. (2013). Big data: What’s your plan?. McKinsey & Company. Retrieved 4 May 2017, from http://www.mckinsey.com/business-functions/digital-mckinsey/our-insight…

McKinsey. (2016). Big data: Getting a better read on performance. McKinsey & Company. Retrieved 29 April 2017, from http://www.mckinsey.com/industries/high-tech/our-insights/big-data-gett…- performance

McLaughlin, P., & Sherouse, O. (2016). The McLaughlin-Sherouse List: The 10 Most-Regulated Industries of 2014. Mercatus Center. Retrieved 21 March 2017, from https://www.mercatus.org/publication/mclaughlin- sherouse-list-10-most-regulated-industries-2014

McMillan, R. (2012). How Social Security Rescued IBM From Death by Depression. WIRED. Retrieved 30 December 2016, from https://www.wired.com/2012/06/how-social-security-saved-ibm/

Mettler, T. (2011). Maturity assessment models: a design science research approach. International Journal Of Society Systems Science, 3(1/2), 81. http://dx.doi.org/10.1504/ijsss.2011.038934

Mettler, T., & Rohner, P. (2009). Situational maturity models as instrumental artifacts for organizational design.

Proceedings Of The 4Th International Conference On Design Science Research In Information Systems And Technology - DESRIST '09. http://dx.doi.org/10.1145/1555619.1555649

Miller, G., Gerlach, S., & Bräutigam, D. (2006). Business intelligence competency centers (1st ed.). Hoboken, N.J.: John Wiley & Sons, Inc.

Morgan, J. (2013). Why Big Company Doesn't Mean Job Security. Forbes.com. Retrieved 21 February 2017, from http://www.forbes.com/sites/jacobmorgan/2013/11/14/why-big-company-does…- security/#35b01c0779fb

Morgan, L. (2016). Rise And Fall Of The Chief Data Officer - InformationWeek. InformationWeek. Retrieved 13 March 2017, from http://www.informationweek.com/strategic-cio/it-strategy/rise-and-fall-…- officer/a/d-id/1324280

Mullany, M. (2016). 8 Lessons from 20 Years of Hype Cycles. LinkedIn. Retrieved 13 April 2017, from https://www.linkedin.com/pulse/8-lessons-from-20-years-hype-cycles-mich…

Nate Silver: What I need from statisticians - Statistics Views. (2013). Statisticsviews.com. Retrieved 30 December 2016, from http://www.statisticsviews.com/details/feature/5133141/Nate-Silver-What…- statisticians.html

Neef, D. (2015). Why haven’t SMEs cashed in on big data benefits yet?. SearchBusinessAnalytics. Retrieved 17 March 2017, from http://searchbusinessanalytics.techtarget.com/feature/Why-havent-SMEs-c…- data-benefits-yet

NewVantage Partners,. (2016). Big Data Executive Survey 2016. Retrieved from http://newvantage.com/wp- content/uploads/2016/01/Big-Data-Executive-Survey-2016-Findings-FINAL.pdf

NIST,. (2015). NIST Big Data Interoperability Framework: Volume 3, Use Cases and General Requirements. Retrieved from http://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.1500-3.pdf

Northouse, P. (2013). Leadership (1st ed., p. 5). Los Angeles [u.a.]: SAGE.

Number of Internet Users (2016) - Internet Live Stats. (2017). Internetlivestats.com. Retrieved 6 February 2017,

from http://www.internetlivestats.com/internet-users/

O'Regan, R. (2014). Chief analytics officer: The ultimate big data job?. Computerworld. Retrieved 21 March 2017, from http://www.computerworld.com/article/2688352/chief-analytics-officer-th…- job.html

Ogbuokiri, B., Udanor, C., & Agu, M. (2015). Implementing bigdata analytics for small and medium enterprise (SME) regional growth. IOSR Journal Of Computer Engineering, Volume 17(Issue 6), 35-43. http://dx.doi.org/10.9790/0661-17643543

Ogden, J., & Lo, J. (2012). How meaningful are data from Likert scales? An evaluation of how ratings are made and the role of the response shift in the socially disadvantaged. Journal Of Health Psychology, 17(3), 350-361. http://dx.doi.org/10.1177/1359105311417192

Paskach, C., & Johnston, D. (2017). Data Analytics Now Cost-Effective For Smaller Firms - Law360. Law360.com. Retrieved 17 March 2017, from https://www.law360.com/articles/893647/data-analytics-now- cost-effective-for-smaller-firms

Philippens, M. (2017). Data & Analytics maturity. Tervuren.

Piech, C. (2013). CS221. Stanford.edu. Retrieved 7 April 2017, from http://stanford.edu/~cpiech/cs221/handouts/kmeans.html

Plato, & Gallop, D. (1988). Phaedo (1st ed.). Oxford [Oxfordshire]: Clarendon Press.

Provost, F. & Fawcett, T. (2013). Data science for business (1st ed.). Sebastopol, Calif: O'Reilly.

PwC,. (2015). Great expectations: The evolution of the chief data officer. Retrieved from https://www.pwc.com/us/en/financial-services/publications/viewpoints/as…

PwC,. (2016). PwC's Global Data and Analytics Survey 2016. Retrieved from http://www.pwc.com/us/en/advisory-services/data-possibilities/big-decis…

Reeves, M. & Pueschel, L. (2015). Die Another Day: What Leaders Can Do About the Shrinking Life Expectancy of Corporations. www.bcgperspectives.com. Retrieved 15 January 2017, from https://www.bcgperspectives.com/content/articles/strategic-planning-gro…

Regalado, A. (2013). Big Data Gets Personal. MIT Technology Review. Retrieved 7 February 2017, from https://www.technologyreview.com/s/514346/the-data-made-me-do-it/

Rouse, M. (2013). What is maturity grid (maturity model)? - Definition from WhatIs.com. WhatIs.com. Retrieved 20 January 2017, from http://whatis.techtarget.com/definition/maturity-model

Rouse, M. (2014). What is Kryder's Law? - Definition from WhatIs.com. SearchStorage. Retrieved 5 March 2017, from http://searchstorage.techtarget.com/definition/Kryders-Law

Rowley, J. (2007). The wisdom hierarchy: representations of the DIKW hierarchy. Journal Of Information Science, 33(2), 163-180. http://dx.doi.org/10.1177/0165551506070706

Samuels, M. (2016). Is this really the end for the chief digital officer? | ZDNet. ZDNet. Retrieved 9 March 2017, from http://www.zdnet.com/article/is-this-really-the-end-for-the-chief-digit…

SAS,. (2007). Five steps to evolving into an intelligent, high- performance enterprise. Retrieved from http://www.eurim.org.uk/activities/ig/voi/IEM.pdf

SAS,. (2013). Big Data in Big Companies. Retrieved from http://www.sas.com/resources/asset/Big-Data-in-Big- Companies.pdf

Sen, D., Ozturk, M., & Vayvay, O. (2016). An Overview of Big Data for Growth in SMEs. Procedia - Social And Behavioral Sciences, 235, 159-167. http://dx.doi.org/10.1016/j.sbspro.2016.11.011

Signal. (2016). Oxford Dictionaty. Retrieved from https://en.oxforddictionaries.com/definition/signal

Simon, P. (2013). Even Small Companies Can Tap Big Data If They Know Where to Look. Harvard Business Review. Retrieved 17 March 2017, from https://hbr.org/2013/12/even-small-companies-can-tap-big-data-if- they-know-where-to-look

Simonite, T. (2016). The foundation of the computing industry’s innovation is faltering. What can replace it?. MIT Technology Review. Retrieved 11 April 2017, from https://www.technologyreview.com/s/601441/moores- law-is-dead-now-what/

STATS | YouTube Company Statistics - Statistic Brain. (2016). Statistic Brain. Retrieved 30 January 2017, from http://www.statisticbrain.com/youtube-statistics/

Steinert, M., & Leifer, L. (2010). Scrutinizing Gartner's hype cycle approach. Technology Management For Global Economic Growth (PICMET). Retrieved from https://www.researchgate.net/publication/224182916_Scrutinizing_Gartner…

Stockton, N. (2016). Elon Musk Announces His Plan to Colonize Mars and Save Humanity. Wired.com. Retrieved 29 April 2017, from https://www.wired.com/2016/09/elon-musk-colonize-mars/

Strategy&,. (2015). Adapt, disrupt, transform, disappear: The 2015 Chief Digital Officer Study. Retrieved from http://www.strategyand.pwc.com/media/file/The-2015-chief-digital-office…

Strategy&,. (2015). Companies without a dedicated leader of digital transformation may lose competitive advantage. Strategyand.pwc.com. Retrieved 8 March 2017, from http://www.strategyand.pwc.com/uk/home/press_contacts/displays/cdo-stud…

Stubbs, E. (2014). Big Data, Big Innovation: Enabling Competitive Differentiation through Busi (1st ed.). John Wiley & Sons.

Suer, M. (2015). Is it the CDO or CAO or Someone Else?. The Informatica Blog - Perspectives for the Data Ready Enterprise. Retrieved 21 March 2017, from https://blogs.informatica.com/2015/01/26/chief-data-officer- cao-someone-else-data-analytics/#fbid=tevSDKjvCQM

Sullivan, D. (2016). Google now handles at least 2 trillion searches per year. Search Engine Land. Retrieved 6 February 2017, from http://searchengineland.com/google-now-handles-2-999-trillion-searches-…

Swanstrom, R. (2014). What Is Big Data? - Blog. Datascience.berkeley.edu. Retrieved 14 December 2016, from https://datascience.berkeley.edu/what-is-big-data

Systems, E. (2014). You Have The Data, But You Need INFORMATION - Effectual Systems. Effectual Systems. Retrieved 2 January 2017, from http://effectualsystems.com/data-need-information/

Taylor, D. (2016). Battle of the Data Science Venn Diagrams. Kdnuggets.com. Retrieved 30 December 2016, from http://www.kdnuggets.com/2016/10/battle-data-science-venn-diagrams.html

TDWI,. (2014). TDWI Analytics Maturity Model Guide. Retrieved from https://tdwi.org/whitepapers/2014/10/tdwi-analytics-maturity-model-guid…

Teigen, R. (1997). Supply Chain Management. Eil.utoronto.ca. Retrieved 4 April 2017, from http://eil.utoronto.ca/wp-content/static/profiles/rune/node5.html

The Abacus: A Brief History. Ee.ryerson.ca. Retrieved 29 December 2016, from http://www.ee.ryerson.ca/~elf/abacus/history.html

The destruction of the Great Library of Alexandria. (2016). Ancient Origins. Retrieved 30 December 2016, from http://www.ancient-origins.net/ancient-places-africa-history-important-…- alexandria-001644

The Royal Swedish Academy of Sciences,. (1997). Press Release. Retrieved from http://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/1997…

Thomas Burke (USA) - 100m. International Olympic Committee. Retrieved 28 February 2017, from https://www.olympic.org/news/speed-merchant-burke-shines-in-the-sprint

Tien, J. (2003). Toward a decision informatics paradigm: a real-time, information-based approach to decision making. IEEE Transactions On Systems, Man And Cybernetics, Part C (Applications And Reviews), 33(1), 102- 113. http://dx.doi.org/10.1109/tsmcc.2003.809345

Tschabitscher, H. (2016). Ever Wonder How Many Emails Get Sent Worldwide Every Day. Lifewire. Retrieved 30 January 2017, from https://www.lifewire.com/how-many-emails-are-sent-every-day-1171210

Vaes, K. (2013). Understanding ; Data, Knowledge, Information & Wisdom. Karim Vaes. Retrieved 11 December 2016, from https://kvaes.wordpress.com/2013/05/31/data-knowledge-information-wisdo…

van Rijmenam, M. (2015). Big Data at Walmart is All About Big Numbers; 40 Petabytes a Day!. Linkedin. Retrieved 14 December 2016, from https://www.linkedin.com/pulse/big-data-walmart-all-numbers-40- petabytes-day-mark-van-rijmenam

Veryard, R. (2005). Technology Hype Curve. Demandingchange.blogspot.be. Retrieved 13 April 2017, from https://demandingchange.blogspot.be/2005/09/technology-hype-curve.html

Walker, M. (2012). Data Veracity. Datasciencecentral.com. Retrieved 14 December 2016, from http://www.datasciencecentral.com/profiles/blogs/data-veracity

Watson, H., Ariyachandra, T., & Matyska, R. (2001). Data Warehousing Stages of Growth. Information Systems Management, 18(3), 42-50. http://dx.doi.org/10.1201/1078/43196.18.3.20010601/31289.6

Wersig, G. & Neveling, U. (1971). Terminology of documentation (1st ed.). Paris: UNESCO.

What Is Big Data? - Gartner IT Glossary - Big Data. (2012). Gartner IT Glossary. Retrieved 14 December

2016, from http://www.gartner.com/it-glossary/big-data/

What’ s the Difference Between Data Science and Statistics?. (2015). Priceonomics. Retrieved 2 January 2017, from https://priceonomics.com/whats-the-difference-between-data-science-and/

White, T. (2012). Hadoop: The Definitive Guide (1st ed.). O'Reilly Media.

Wiggins, C., Hand, D., Bennett, F., Wolfe, P., & Ghahramani, Z. (2015). Data Science and Statistics: different

worlds?. YouTube. Retrieved 15 January 2017, from https://www.youtube.com/watch?v=C1zMUjHOLr4

Wilfong, K. & Vagata, P. (2016). Scaling the Facebook data warehouse to 300 PB. Facebook Code. Retrieved 14 December 2016, from https://code.facebook.com/posts/229861827208629/scaling-the-facebook-da…- warehouse-to-300-pb/

Wisdom. (2016). Oxford Dictionary. Retrieved from https://en.oxforddictionaries.com/definition/wisdom Wolchover, N. (2016). Top 10 Inventions that Changed the World. Live Science. Retrieved 28 February 2017,

from http://www.livescience.com/33749-top-10-inventions-changed-world.html

Wolfe, P. (2015). Data Science and Statistics: different worlds?. YouTube. Retrieved 15 January 2017, from https://www.youtube.com/watch?v=C1zMUjHOLr4

Xu, F., Zhan, H., Huang, W., Luo, X., & Xu, D. (2016). The value of Chief Data Officer presence on firm performance. Retrieved from http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1364&context=pacis2…

Zeleny, M. (1987). Management support systems: towards integrated knowledge management. Human Systems Management, 7(1), 59-70.

Zeleny, M. (2013). Integrated Knowledge Management. International Journal Of Information Systems And Social Change, 4(4), 62-78. http://dx.doi.org/10.4018/jissc.2013100104

Zikopoulos, P., deRoos, D., Bienko, C., Buglio, R., & Andrews, M. (2015). Big data beyond the hype (1st ed.). Mc Graw Hill Education.

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Universiteit of Hogeschool
Universiteit Antwerpen
Thesis jaar
2017
Promotor(en)
Koen Vandenbempt