Contents |
Executive Summary
Is data a strategic opportunity or a challenge that needs to be managed? The discourse of whether data is an opportunity or constraint for the enterprise has changed dramatically over the last several years and has begun to shift toward data becoming a source of organizational value. However IT managers continue to struggle with data as a challenge that must be managed.
In our latest survey with the Wikibon community, data growth, security, & protection, along with regulatory issues dominate the top challenges for enterprise IT buyers, above any discussion of cloud, mobile, or social. While the latter remain strategic, how to manage data is a decision for today and has broader implications for future architectures if not addressed.
Top IT Challenges for the Enterprise
The burden of data growth within the enterprise is an overarching challenge for IT buyers in 2012. Highlights of the survey data include:
- “Data Growth” and “Excessive Data Growth” are rated as the third & fourth challenges for IT buyers, just below the overarching challenges around “Budget Constraints” and “Inability for IT to respond to the business in a timely manner”.
- Secondary concerns are also related to storage growth – security, data protection, compliance, and cloud.
- Tertiary concerns among IT buyers are mobility, staffing, modernizing the application portfolio, and desktop transformation.
IT Buyer and IT Vendor Mis-match
In contrast, IT vendors perceive cloud and mobility as top challenges:
- There is also a dissonance between buyers and sellers in the area of compliance. Regulatory compliance has substantive business implications for customers if not addressed (fines, credibility, loss of revenue).
- Surprisingly, cloud and mobility, while important strategically, are not cited by Wikibon practitioners as having the same near-term pressing imperative.
These findings underscore how pressing the need is among enterprise IT buyers to address data growth and manageability challenges at their organization. Data has become the critical enabler (and potentially biggest inhibitor) for the future datacenter.
Wikibon believes that much of the future value derived from data will come from “Big Data” projects, designed specifically to extract insight and predict organizational opportunities. Engineering these projects will, at its core, require matching internal organizational data with external metrics and data sources. Without sound data management approaches and a sensible data architecture, organizations will be constrained, and future value extraction for enterprises will be severely limited.
The bottom line is data is both a challenge and an opportunity for CIOs. Unmanaged growth leads to major exposure around failed backups, dubious recovery procedures, information risk, expensive band-aid solutions, and most importantly, failed business opportunities
Understanding the Challenges of Big Data
IT buyers face TWO overarching challenges as they contemplate Big Data projects – analytics and data value. These two major themes should, at the very least, be addressed in all vendor messaging and should be used to help customers “sell” Big Data solutions internally.
- Analytics and Insights: Concerns about being able to derive insights through data analytics account for most of the thinking around Big Data implementation challenges. This is not surprising, given that the Big Data market is still relatively nascent and that early market development has overwhelmingly focused on platforms and infrastructure rather than analytics and applications. IT buyers associate the ongoing challenge of implementing Big Data analytics with data restructuring, using the latest/greatest data as well as the need to hire skilled data scientists.
- Data “Value”: IT buyers also see a distinct set of challenges involving conveying data “value” to the broader organization. Understanding what data to keep and throw away, how to monetize the data, how to create a culture of trust internally so that analytics are even on the radar, as well as how to implement visualization tools, are seen on par with the logistics of dealing with data volume. IT organizations typically have to build credibility around new enterprise technology products in order to drive momentum in investments. An executive sponsor or champion is always necessary to drive credibility and, ultimately, funding. While it is not surprising that IT buyers view monetizing data as part of demonstrating value, monetizing the data will actually come from delivering insights and analytics to build a business case.
Big Data is an Indicator of IT Transformation Intensity
Statistically, both of these Big Data challenges – analytics and value - predict the level of IT transformation that is required by the customer. This means that the greater the perceived challenge of deploying Big Data solutions for the IT buyer, the greater the level of new investment around IT transformation that will be necessary.
This finding explains the level of IT buyers' focus on conveying data “value” and why customers see overcoming the challenges of analytics as critical.
Takeaway: Cost reduction, doing more will less and more efficient IT are becoming "table stakes." Given that IT buyers recognize that Big Data investments will require substantial technology transformation, the focus of building a business case must evolve toward business benefit and not solely focus on more traditional metrics such as TCO. Practitioners should prioritize working with suppliers that can help them understand business value and create solid "proof-cases" that monetize the advantages of leveraging data to improve time-to-market or the creation of new business models that are transaction oriented, rather than just cost reduction.
Methodology
In the summer of 2012, the Wikibon community, in collaboration with SiliconAngle’s ServicesAngle, launched its inaugural IT Transformation Survey, targeting a random sample of business technology professionals drawn from the Wikibon community. After an initial outreach to the Wikibon practitioner community via email, social media was used to solicit respondents. We received 216 responses, the vast majority of which came from the Wikibon email outreach. The survey was completed over the Internet using a SurveyMonkey Web questionnaire with an incentive drawing. Analysis of the data involved multivariate techniques, including factor analysis and logistic regression analysis provided by the SiliconAngle/Wikibon data science team.
Action Item: Data is both an opportunity and a management imperative. The former has transformative and strategic value that can drive revenue while the latter reduces cost and risk. IT organizations (ITOs) must increasingly pursue data as an opportunity and find ways to demonstrate that data has monetary value. By creating value from data, ITOs will get required budget to both manage data and more importantly, transform data for organizational benefit. Measuring the value of data is hard. ITOs should look to suppliers who have the sophistication and services to measure the business value of technology and to demonstrate how transforming their data management approach will enable them to be more responsive to business demands as well as avoid becoming less competitive than their peers.
Footnotes: