Turning Data Into Competitive Advantage: Enterprise Strategy
This paper examines how enterprises can move beyond information overload by developing coherent strategic frameworks that give meaning to the vast volumes of data generated through Big Data systems, cloud computing, and social networks. Rather than advocating for more technology, the paper argues that Business Process Management (BPM) frameworks must underpin all IT investments, ensuring that data initiatives align with core business strategies. It reviews the evolving role of the Chief Information Officer, the implications of high-performance analytics platforms such as Hadoop, and the contextual intelligence that social networks provide. The paper concludes that data, like fuel, only drives an organization forward when paired with disciplined strategic focus.
- Introduction: The Information Overload Challenge: Why technology alone cannot solve data overload
- Making Data Strategic With a Solid Organizational Framework: BPM frameworks and the CIO's evolving strategic role
- Big Data, Cloud Computing, and the Data Explosion: Hadoop, MDM, and social networks as strategic tools
- Conclusion: Strategy as the Engine, Data as the Fuel: Data needs strategic frameworks to create real value
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What makes this paper effective
- The paper uses a consistent extended metaphor — data as fuel — that anchors its central argument and makes an abstract concept concrete and memorable.
- It connects technology trends (Hadoop, cloud computing, social networks) directly to organizational behavior and strategy, avoiding purely technical description.
- Citations draw from a mix of practitioner publications (InformationWeek, Computerworld) and academic journals (MIT Sloan Management Review, Journal of Knowledge Management), lending both credibility and real-world grounding.
Key academic technique demonstrated
The paper demonstrates synthesis across practitioner and scholarly sources to build a single cohesive argument. Rather than summarizing each source in sequence, the writer weaves multiple references together within each paragraph to support a unified claim — for example, using Kalpic & Bernus (2006) alongside Collett (2011) to show that process frameworks must precede technology investment. This technique elevates the paper from a literature summary into a genuine argumentative essay.
Structure breakdown
The paper opens with a problem statement identifying information overload and the limitations of technology-first responses. The second section develops the organizational framework solution, centering on BPM and the strategic role of the CIO. The third section surveys the Big Data landscape — Hadoop, cloud, social networks, MDM — and argues these tools only deliver value within a strategic process context. The conclusion returns to the central metaphor, reinforcing that frameworks and focus, not data volume, drive competitive advantage.
Introduction: The Information Overload Challenge
Given the exponential increase in data being generated across enterprise systems, social networks, and legacy IT infrastructure, ensuring that a consistent set of frameworks and objectives is used to bring relevance to this data has become critical. The tendency to "boil the ocean" of data through Big Data initiatives — including Hadoop, an open-source analytics platform — has recently emerged as one viable alternative (McKendrick, 2012). Yet too often the ability to ingest literally terabytes of data and analyze it is of limited use without a consistent, strategic framework to make use of it (Rogers, 2011). Too many IT organizations fall victim to speeding up mediocre reporting and analysis processes without first thinking about how to bring greater value to their strategic initiatives through that data (Daly, 2011). The answer to this dilemma is not found in more technology; it is found in creating a more effective strategic framework to bring meaning to the data (Kalpic & Bernus, 2006).
References
Bernoff, J., & Li, C. (2008). Harnessing the power of the oh-so-social web. MIT Sloan Management Review, 49(3), 36–42.
Bughin, J., Chui, M., & Manyika, J. (2010). Clouds, big data, and smart assets: Ten tech-enabled business trends to watch. The McKinsey Quarterly, (4), 26.
Collett, S. (2011). Why big data is a big deal. Computerworld, 45(20), 18–20, 22, 24.
Daly, R. (2011). The key to big data mastery. Waters, 22–25.
Greengard, S. (2012). Big data unlocks business value. Baseline, (114), 20–23.
Henschen, D. (2011). Big data: Fast, complex, varied, costly. InformationWeek, (1311), 22–29.
Kalpic, B., & Bernus, P. (2006). Business process modeling through the knowledge management perspective. Journal of Knowledge Management, 10(3), 40–56.
LaValle, S., Lesser, E., Shockley, R., Hopkins, M. S., & Kruschwitz, N. (2011). Big data, analytics and the path from insights to value. MIT Sloan Management Review, 52(2), 21–32.
McKendrick, J. (2012). Hadoop enters the enterprise mainstream, and big data will never be the same. Database Trends and Applications, 26(1), 4–6, 8.
Rogers, S. (2011). Big data is scaling BI and analytics. Information Management, 21(5), 14.
Strenger, L. (2008). Coping with "big data" growing pains. Business Intelligence Journal, 13(4), 45–52.
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