Big Data

KPMG Survey: Firms Struggle with Big Data

Bill Schmarzo By Bill Schmarzo CTO, Dell EMC Services (aka “Dean of Big Data”) February 6, 2014

A recent KPMG study[1] reveals that not even ten percent of businesses believe they are in a position to make use of the information they have on customer preferences, behaviors, and demands. Some relevant observations from the study include:

  • 85 percent of the 144 CFOs and CIOs questioned for the “Going beyond the data” survey said that they don’t know how to analyze the data they have already collected.
  • 54 percent said their greatest barrier to success was an inability to identify the data worth collecting.

“Most organisations are unable to connect the dots because they do not fully understand how data and analytics can transform their business,” said Alwin Magimay, head of digital and analytics for KPMG UK.

Data, Data Everywhere And Not A Drop of Insights

These results are consistent with what I see when I talk to customers:  organizations struggle with identifying where and how to start their big data journeys. There are opportunities to help organizations 1) analyze the “dark” data that they already have, but is currently buried in their operational systems and data warehouses; and 2) identify and prioritize other internal and external data sources that they could leverage to optimize existing business processes and uncover new monetization opportunities. Perfect for our Vision Workshop approach.

These are the reasons we developed the Vision Workshop data insight envisioning and prioritization process. The Vision Workshop helps organizations that “don’t know how to analyze the data they have already collected” and lack the ability “to identify the data worth collecting.” In particular, the Vision Workshop:

  • Institutes a formal process for identifying where data analytics can drive material business impact that affects the organization’s key business initiatives or challenges.
  • Ensures business relevance by focusing the workshop process on a key business initiatives or business opportunity.
  • Employs facilitation techniques and exercises to envision the “realm of what’s possible” from the organization’s structured and unstructured internal data, as well as exploring the business potential of external data.
  • Drives business and IT alignment around those “best” analytic opportunities with a clear roadmap of what needs to be done.

The Vision Workshop: Envisioning The Realm of Possibilities

First, the Vision Workshop is not a one-day effort. While the Vision Workshop process does conclude in a half-day workshop, there is a substantial amount of work that needs to be done prior to the actual workshop. The image below (figure 1) lays out the process, but they key activities that need to happen prior to the workshop include:

  • Identifying the business initiative or business challenge upon which to focus the workshop. This is a critical first step as it 1) defines the business stakeholders who will need to participate in the workshop, and 2) identifies the data that will be used to build out the illustrative analytic examples.
  • Conducting business interviews with stakeholders to capture key business objectives, the decisions that they are trying to make, and the types of questions that they need to answer in support of those decisions.
  • Grabbing a small sample set of data so that the data scientist can build some illustrative analytics (to drive the “realm of the possible” brainstorming session).
  • Creating simple mockups that show how the resulting analytics might manifest themselves within the business stakeholder environment.
Figure 1: Vision Workshop Process

Figure 1: Vision Workshop Process

The Ideation Workshop

Once the activities described above have been completed (which typically takes about 2 weeks of work), we are now ready for the half-day ideation workshop. The workshop helps the participants:

  • Go beyond just reporting so that the business stakeholders understand how to analyze the data they have already collected.
  • Put in place a process driven to help the business stakeholders identify additional data worthy of collecting.

While the free-form brainstorming is exciting and even exhilarating, we still need to bring the process back to identify those specific use cases which we can address today. The prioritization process identifies those use cases, and the supporting analytics and data where the business value is worthwhile and the feasibility of success is high (see figure 2).

Figure 2:  Prioritization Matrix

Figure 2: Prioritization Matrix

The Vision Workshop process gives us a framework against which we can make decisions about how to leverage our existing data, as well as identifying additional data sources that can provide value against our targeted business initiative. As you can see from figure 3, we can implement a process for evaluating the value of different internal and external data sources against the value drivers for the targeted business initiative; that is, those “levers” that the business can turn in order to make more money (for example:  increase store traffic, increase market basket size, or increase up-sell/cross-sell).

Figure 3: Data Source Value Assessment

Figure 3: Data Source Value Assessment

Summary

Organizations are struggling with where and how to start their Big Data journeys. In particular, organizations are struggling with:

  • Understanding how to analyze the data they have already collected
  • Putting in place a process to identify additional data worth collecting
Figure 4:  Big Data Vision Workshop

Figure 4: Big Data Vision Workshop

The Vision Workshop process (see figure 4) is designed to address these issues with a simple, but effective process based upon the assumption that both technology and data decisions should be driven by the business. As we like to say, organizations don’t need a Big Data strategy; they need a business strategy that incorporates Big Data.

 


Bill Schmarzo

About Bill Schmarzo


CTO, Dell EMC Services (aka “Dean of Big Data”)

Bill Schmarzo, author of “Big Data: Understanding How Data Powers Big Business” and “Big Data MBA: Driving Business Strategies with Data Science”, is responsible for setting the strategy and defining the Big Data service offerings and capabilities for Dell EMC Services Big Data Practice. As the CTO for the Big Data Practice, he is responsible for working with organizations to help them identify where and how to start their big data journeys. He’s written several white papers, is an avid blogger and is a frequent speaker on the use of Big Data and data science to power the organization’s key business initiatives. He is a University of San Francisco School of Management (SOM) Executive Fellow where he teaches the “Big Data MBA” course. Bill was ranked as #4 Big Data Influencer by Onalytica.

Bill has over three decades of experience in data warehousing, BI and analytics. Bill authored Dell EMC’s Vision Workshop methodology that links an organization’s strategic business initiatives with their supporting data and analytic requirements, and co-authored with Ralph Kimball a series of articles on analytic applications. Bill has served on The Data Warehouse Institute’s faculty as the head of the analytic applications curriculum.

Previously, Bill was the vice president of Analytics at Yahoo where he was responsible for the development of Yahoo’s Advertiser and Website analytics products, including the delivery of “actionable insights” through a holistic user experience. Before that, Bill oversaw the Analytic Applications business unit at Business Objects, including the development, marketing and sales of their industry-defining analytic applications.

Bill holds a masters degree in Business Administration from the University of Iowa and a Bachelor of Science degree in Mathematics, Computer Science and Business Administration from Coe College.

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2 thoughts on “KPMG Survey: Firms Struggle with Big Data

  1. Interesting take. I for one believe these types of studies more than the Gartner ones that claim that 2/3 or companies are already “doing” Big Data. Now is precisely the time to act.

  2. Totally agree Phil. The vast majority of companies that I talk to aren’t doing anything significant with big data (95%+). Heck, many are still being held captive by the data warehouse and business intelligence investments.

    The time to act is now!