Veri Kültürü Oluşturmada Dijital Dönüşüm Liderlerinin Önceliklerinin Belirlenmesi

Gelişen teknolojiyle birlikte her geçen gün daha fazla veri üretilip, daha kolay saklanabilmekte ve de daha hızlı analiz edilerek değere dönüştürülebilmektedir. Bu değerin farkına varan geleneksel kurumlar gerek iş süreçlerini gerekse üretim yöntemlerini dijitale dönüştürme çalışmalarına başlamıştır. Organizasyonların Dijital Dönüşüm sürecini yönetmede CIO (Chief Information Officer - Bilişim Üst Düzey Yöneticileri), CAO (Chief Analytics Officers - Veri Analitik Yöneticileri)  ve CDO (Chief Data Officers - Dijital Dönüşüm Liderleri) gibi pozisyonlarda çalışan yöneticiler ön plana çıkmaktadır. Bu yöneticiler, kurumlarının veri stratejilerini geliştirmek ve veri ekosistemini yönetmekle yükümlüdür. Diğer bir yükümlülükleri ise çalışanlarını verinin gücü ve olanaklarıyla ilgili olarak eğitmektir. Böylelikle veri kültürüne sahip olacak kurumlar veri kullanımlarını yeniden şekillendirebilecek, dijital iş stratejileri geliştirebileceklerdir. Bu çalışmada Türkiye’de faaliyet gösteren büyük ölçekli organizasyonların CIO, CAO ve CDO pozisyonlarında görev yapan kişilerine yönelik bir araştırmayla, organizasyonlarında dijitalleşme açısından hangi kriterlere önem verdikleri ölçülmeye çalışılmıştır. Ana (Paydaş, Teknolojik, Finansal ve Yönetsel) ve alt kriterlerin önem dereceleri Analitik Hiyerarşi Prosesi ile belirlenmiştir. Araştırma, ileriki çalışmalarda oluşturulacak bir veri kültürü modeli için bir ilk çalışma özelliği taşımaktadır.

Determining The Priorities of Chief Data Officers for Building Data Culture

New business models are revealed by digitization world. With a data-driven business approach, organizations must keep pace with digital transformation. Digital transformation will be facilitated with the Data Culture, which is a work environment based on data, to be formed in organizations. In this study, the hierarchical structure was constituted for data culture. The hierarchy consists of four main criteria and 17 sub-criteria. The main criteria (dimensions) are defined as organizational factors, stakeholders (such as customers, suppliers, business partners), financial factors, and technological factors. With this study, it is aimed to find out what criteria are most important for the managers who responsible for digital transformation in their data culture building process.    Analytic Hierarchy Process (AHP) designed questionnaire survey has reached managers who work as in CIO, CAO, and CDO positions at different industries. Main and sub-criteria weights were determined by using the AHP. The results of the AHP analysis revealed that managers attach the most important to the stakeholder dimension in creating data culture and give the least importance to the financial dimension. In the sub-criteria, it was most important to obtain the ability of Stakeholder-driven business while the increase in the profitability of organization was the least significant.

___

  • Accenture Turkey Digitization Index 2016. (2017). https://www.accenture.com/_acnmedia/PDF-48/Accenture-Turkey-Digi-Ind-Report-English.pdfla=en#zoom=50 Accessed 05 January 2019.
  • Andriole, S. J., Cox, T., & Khin, K. M. (2017). The Innovator’s Imperative Rapid Technology Adoption for Digital Transformation, CRC Press Taylor & Francis Group.
  • Arkhipova, D., & Bozzoli, C. (2018). Digital Capabilities. In G. Bongiorno, D. Rizzo, & G. Vaia (Eds.), CIOs and the Digital Transformation (pp.121-146). Springer.
  • Ashwell, M. L. (2017). The Digital Transformation of Intelligence Analysis, Journal of Financial Crime, Vol. 24, No. 3: 393-411. https://doi.org/10.1108/JFC-03-2017-0020.
  • Bange, C., Handford, M. & Janoschek, N. (2014). Information Culture Leveraging the Power of Collective Intelligence for Better Decision Making, BARC Research Study, BARC Institute.
  • Becerra, J. (2017). The Digital Revolution Is Not About Technology – It’s About People, https://www.weforum.org/agenda/2017/03/the-digital-revolution-is-not-about-technology-it-s-about-people/ Accessed 16 December 2018.
  • Bharadwaj, A., El Sawy, O. A., Pavlou, P. A., & Venkatraman, N. (2013). Digital Business Strategy: Toward a Next Generation of Insights, MIS Quarterly, Vol. 37 No. 2: 471-482.
  • Bladt, J., & Filbin, B. (2014). Who’s Afraid of Data-Driven Management, Harvard Business Review, https://hbr.org/2014/05/whos-afraid-of-data-driven-management Accessed 22 December 2018.
  • Bongiorno, G., Rizzo, D., & Vaia, G. (2018), CIOs and the Digital Transformation: A New Leadership Role. In G. Bongiorno, D. Rizzo, & G. Vaia (Eds.), CIOs and the Digital Transformation (pp.1-9). Springer.
  • Brynjolfsson, E., Hitt, L. M. & Kim, H. H. (2011). Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance?, Available at SSRN: http://ssrn.com/abstract =1819486.
  • Brynjolfsson, E., & McElheran, K. (2016). The Rapid Adoption of Data-Driven Decision-Making, American Economic Review, Vol. 106, No. 5, 133-139. 10.1257/aer.p20161016.
  • Chandler, N., Hostmann, B., Rayner, N., & Herschel, G. (2011). Gartner’s business analytics framework, Gartner, https://www.gartner.com/imagesrv/summits/docs/na/business-intelligence/gartners_business_analytics__219420.pdf Accessed 12 January 2019.
  • Chen, D. Q., Preston, D. S., & Xia, W. (2010). Antecedents and Effects of CIO Supply-Side and Demand-Side Leadership: A Staged Maturity Model, Journal of Management Information Systems, Vol.27, No.1: 231-272. https://doi.org/10.2753/MIS0742-1222270110
  • Davenport, T. H., & Bean, R. (2018). Big Companies Are Embracing Analytics, But Most Still Don’t Have a Data-Driven Culture, Harvard Business Review, https://hbr.org/2018/02/big-companies-are-embracing-analytics-but-most-still-dont-have-a-data-driven-culture Accessed 22 December 2018.
  • Davenport, T. H. (2014). Big Data At Work: Dispelling The Myths, Uncovering The Opportunities, Boston: Harvard Business Review Press.
  • Downes, L., & Nunes, P. F. (2013). Big Bang Disruption, Harvard Business Review, Vol. 91, No. 3: 44-56.
  • Econsultancy (2017). Digital Intelligence Briefing: 2017 Digital Trends. https://econsultancy.com/reports/digital-intelligence-briefing-2017-digital-trends/ Accessed 07 January 2019.
  • EIU (2013). Fostering a Data-Driven Culture, A report from the Economist Intelligence Unit.
  • Gartner Inc. (2017). Mastering the New Business Executive Job of the CIO, Insights From the 2018 CIO Agenda Report. https://www.gartner.com/imagesrv/cio-trends/pdf/cio_agenda_2018.pdf Accessed 24 December 2018.
  • Gartner Press Releases (2018). Gartner Says Global IT Spending to Grow 3.2 Percent in 2019, https://www.gartner.com/en/newsroom/press-releases/2018-10-17-gartner-says-global-it-spending-to-grow-3-2-percent-in-2019 Accessed 24 December 2018.
  • HBR (2012). The Evolution of Decision Making: How Leading Organizations Are Adopting a Data-Driven Culture. Harvard Business Review Analytic Services Report https://hbr.org/resources/pdfs/tools/17568_HBR_SAS%20Report_webview.pdf Accessed 28 December 2018.
  • Hartmann, P. M., Zaki, M., Feldmann, N., & Neely, A. (2014). Big Data for Big Business? A Taxonomy of Data-driven Business Models used by Start-up Firms, University of Cambridge, Cambridge Service Alliance.
  • Kane, G. C., Palmer, D., Phillips, A. N., Kiron, D., & Buckley, N. (2015). Strategy, Not Technology, Drives Digital Transformation, MIT Sloan Management Review and Deloitte University Press, Vol. 14: 1-25.
  • Kohli, R., & Johnson, S. (2011). Digital Transformation in Latecomer Industries: CIO and CEO Leadership Lessons from Encana Oil & Gas (USA) Inc., MIS Quarterly Executive, Vol. 10, No. 4.
  • Kniberg, H. (2014). Spotify Engineering Culture, https://labs.spotify.com/2014/03/27/spotify-engineering-culture-part-1/ Accessed 24 December 2018.Knickrehm, M., Berthon, B., & Daugherty, P. (2016). Digital disruption: The growth multiplier Optimizing digital investments to realize higher productivity and growth. https://www.accenture.com/t00010101T000000__w__/br-pt/_acnmedia/PDF-14/Accenture-Strategy-Digital-Disruption-Growth-Multiplier-Brazil.pdf Accessed 11 January 2019.
  • Lycett, M. (2013). Datafication: Making sense of (big) data in a complex world. European Journal of Information Systems, Vol. 22, No. 4: 381-386. https://doi.org/10.1057/ejis.2013.10.
  • Matt, C., Hess, T. & Benlian, A. (2015). Digital Transformation Strategies, Business Information System Engineering, Vol. 57, No. 5: 339-343. 10.1007/s12599-015-0401-5.
  • Mayer-Schönberger, V., & Cukier, K. (2013). Big data: a revolution that will transform how we live, work, and think, New York: Houghton Mifflin Hartcourt Publishing.
  • McAfee, A., & Brynjolfsson, E. (2012). Big Data: The Management Revolution, Harvard Business Review, http://tarjomefa.com/wp-content/uploads/2017/04/6539-English-TarjomeFa-1.pdf Accessed 16 January 2019.
  • Patil, D.J., & Mason, H. (2015). Data Driven Creating a Data Culture, O’Reilly Media, https://www.oreilly.com/ideas/data-driven Accessed 18 January 2019.
  • Patil, D. J. (2011). Building Data Science Teams, O'Reilly Media.
  • Ramaswamy, P. (2015). How to Create a Data Culture, Cognizant 20-20 Insights White Paper, https://www.cognizant.com/InsightsWhitepapers/how-to-create-a-data-culture-codex1408.pdf Accessed 09 January 2019.
  • Remane, G., Hanelt, A., Nickerson, R. C., & Kolbe, L. M. (2017). Discovering Digital Business Models in Traditional Industries, Journal of Business Strategy, Vol. 38, No. 2: 41-51, https://doi.org/10.1108/JBS-10-2016-0127.
  • Rogers, D. L. (2016). The digital transformation playbook, Rethink your business for the digital age, New York: Columbia University Press.
  • Saaty, T. L. (1990). How to make a decision: The Analytic Hierarchy Process, European Journal of Operational Research, Vol. 48, No. 1: 9-26.
  • Saaty, T. L. (2008). Decision Making with the Analytic Hierarchy Process, Int. J. Services Sciences, Vol. 1, No. 1: 83-98.
  • Saaty, T. L., & Vargas, L. G. (2012). Models, Methods, Concepts & Applications of the Analytic Hierarchy Process. (2nd ed.), Springer.
  • Schalekamp, J., Schalekamp, M., & Manintveld, B. (2015). Today’s Organizational Challenge From Gut Feeling to Data-Driven Decision Making, Deloitte, https://www2.deloitte.com/content/dam/Deloitte/nl/Documents/deloitte-analytics/deloitte-nl-data-analytics-todays-organizational-challenge.pdf Accessed 11 January 2019.
  • Schrage, M. (2014). Embedding Analytics for Growth: Creating a Data-Driven Culture, Harvard Business Review, https://hbr.org/webinar/2014/12/embedding-analytics-for-growth-creating-a-data-driven-culture Accessed 26 December 2018.
  • Shiau, Y., Tsai, T., Wang, W., & Huang, M. (2002). Use Questionnaire and AHP Techniques to Develop Subcontractor Selection System, International Symposium on Automation and Robotics in Construction 19th (ISARC). Proceedings, National Institute of Standards and Technology, Gaithersburg, Maryland: 35-40.
  • Singh, A., & Hess, T. (2017). How Chief Digital Officers Promote the Digital Transformation of their Companies, MIS Quarterly Executive, Vol. 16, No. 1.
  • TUSIAD, (2017b), Türkiye’nin Sanayide Dijital Dönüşüm Yetkinliği, The Boston Consulting Group, No: TÜSİAD-T/2017, 12 – 589.
  • TUSIAD, (2017a), Türkiye’nin Küresel Rekabetçiliği için Bir Gereklilik Olarak Sanayi 4.0, The Boston Consulting Group, No: TÜSİAD-T/2016-03/576, Mart 2016.
  • Verbeke, W., Baesens, B., & Bravo, C. (2018). Profit-Driven Business Analytics, A Practitioner’s Guide to Transforming Big Data into Added Value, New Jersey: John Wiley & Sons.
  • Vesset, D., Morris, H. D., & Gantz, J. F. (2014). Capturing the 1,6 Trillion Data Dividend, IDC White Paper
  • WEF (2016). Digital Transformation of Industries: Digital Enterprise, World Economic Forum White Paper In collaboration with Accenture, https://www.accenture.com/_acnmedia/Accenture/Conversion-Assets/WEF/PDF/Accenture-Digital-Enterprise.pdf Accessed 05 January 2019.