Home > Blogs > VMware Accelerate Advisory Services > Monthly Archives: April 2014

Monthly Archives: April 2014

CIOs Need to Restructure to Deliver Today’s Innovations

No doubt you’ve heard the argument that CIOs are merely technology brokers who “don’t matter” in the world of digital business. We all know that the opposite is true: CIOs who understand the intersection of business and technology matter more than ever. What also matters is that you understand when it’s time to change your organization to meet the needs of the business.

infoweek coverTake a moment to check out this InformationWeek report, which provides practical advice on when and why to restructure, what guiding principles apply, how to get help, and where it pays to take some calculated risks.

Related: Infographic distills 2014 Strategic CIO Survey results

CIO Survey Gives 4 Tips to Tech Execs

This infographic distills InformationWeek’s 2014 Strategic CIO Survey results into top focus areas. Perhaps not surprisingly, for IT execs, cutting costs ranks at the top of the list. What else keeps your peers awake at night? Speed to market, insufficient budgets, and the skills gap. Scroll through the entire image for a final section of practical advice, and share your thoughts and tips in the comments.InformationWeek Infographic_The-Transformative-CIO

Identifying Cost Savings with Service-Based IT Cost Modeling

By Reginald Lo

ReginaldLo-cropResponsible service provisioning requires an appropriate balance between quality and cost. But this balance cannot be achieved without a clear understanding of the service costs and the relationship between cost and service levels. With this knowledge comes the power to make decisions on where and how to spend to reach the desired balance.

To achieve this, you need to:

  • Create a cost model for a service and thereby
  • Understand what contributes to costs
  • Provide levers and/or options for the business to control costs within acceptable service levels.

The major activities in this approach are:

Reg-service-based cost modeling

The availability of the right information, along with processes and procedures for capturing and maintaining the information, is critical to the success of this approach. However, I have found that many of my customers do not have all the information they need and their information processes usually need to be strengthened. Hence, you may want to conduct a pilot first with a small subset of services, identifying the information and process gaps, and creating and executing plans to address the gaps, before applying this approach to a broader set of services.

This approach can be used prior to or in parallel with a cost transparency / show-back / charge-back IT financial management assessment to prepare your IT organization to track and understand service-based costs and help prepare the business for taking a more direct role in making IT cost decisions. It provides the business with levers to control their IT spend.

IT cost modeling is not simple – information may be missing and creative solutions may be required to estimate certain costs; policies need to be established on how to categorize and track costs, and repeatable procedures for creating and maintaining the cost model must be established. However, if IT cost modeling is done well, the benefits of true transparency and effective cost controls can far outweigh the challenges.


Reginald Lo is Director of Service Management Transformation with VMware Accelerate Advisory Services and is based in California.

Big Data: Big Opportunity or Big Challenge?

By Barton Kaplan

We are undoubtedly living in the era of big data. For any doubters, McKinsey estimates that the amount of new data that enterprises around the world stored on disk drives in 2010 equaled 7 exabytes, growing at a compound annual rate of 40 percent.[1]

The opportunities for enterprises to leverage this data abound, at least in theory. In the retail sector alone, McKinsey estimates that big data could raise operating margins by a whopping 60 percent.[2] And in US healthcare, the potential benefits are as much as USD $300B annually.[3] Further, venture capital is flowing to a slew of new startups that are creating tools and algorithms that can parse data at scale.

But the reality inside enterprises paints a different picture. The biggest misconception with big data is that the sheer volume means there is more meaningful insight to be had. But as Nassim Taleb has convincingly shown, as the amount of data goes up, the signal to noise ratio goes down, by as much as 200 times.[4]

This phenomenon is reflected in corporate survey data. In a poll of over 8,000 employees by CEB, only a third indicated that the information they needed to do their jobs was available. And less than half said that corporate sources of information were usable.[5]

Meanwhile, at a time when over 80 percent of employees at the typical organization are now considered knowledge workers, fewer than 40 percent have the combination of analytical skills and judgment needed to use that data to drive better decisions,[6] without which no value can be gained. Data scientists alone can’t make up for a capability gap across the broader employee base.

So how do organizations tackle the myriad information management challenges that big data has exacerbated so they can realize some of the benefits? In my work with companies, the following four tactics have proved effective:

  1. Elevate the importance of information: One large financial institution put information on par with people, process, and technology as a discrete enabler of business capabilities, leading to a fully funded, five-year information management strategy and roadmap.
  2. Develop differently for data: At a major insurance company, IT leadership replaced their software development lifecycle with a data-centric development lifecycle for information-intensive projects.
  3. Make data analysis user-friendly: IT can no longer keep up with business demand for reports and dashboards. Instead of being the bottleneck, work instead to expose corporate data in a secure yet user-friendly manner so employees can quickly and easily generate their own reports. At one organization I worked with, they set up an interface modeled on Amazon’s with the motto “shopping for data.” The result was a 50 percent reduction in support staff time to deliver analytic services.
  4. Upskill your people: Rather than trying to land a few hard to find, expensive data scientists, focus instead on raising the skill sets of the 8 out of 10 employees in your organization who are considered knowledge workers. This starts with an understanding of the profile of an employee with high “insight IQ.” Try the following quiz to see if you fit the bill.


Barton Kaplan is a business solution strategist with VMware Accelerate Advisory Services and is based in Maryland.

[1] McKinsey Global Institute, “Big data: The next frontier for innovation, competition, and productivity,” June 2011.
[2] Ibid.
[3] Ibid.
[4] Nassim Taleb, “Noise and Signal—Nassim Taleb,” Farnam Street Blog, 29 May 2012.
[5] CEB, Business Outcomes from Big Data, Webinar, March 2014.
[6] CEB Enterprise Architecture Leadership Council, “Overcoming the Insight Deficit,” 2011.