3 Leading Practice Brief - Analytics at Dell Services (2)

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Leading Practice Brief #3
Analytics at Dell Services
April 2013
Authored by:
IIA Faculty

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Analytics at Dell Services, April 2013
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Introduction
As analytics groups and the businesses they serve grow and evolve, many find that they need to
reconsider their organizational structures and collaboration models. There is no one-size-fits-all
solution to the organizational structure question. The DELTAi
model defined by IIA co-founder,
Tom Davenport, and faculty members Robert Morison and Jeanne Harris indicates that the
optimal structure is influenced by the quality and accessibility of data, enterprise orientation,
analytical leadership, strategic targets for analytics, and the talented analysts to build and
maintain the models.
This leading practice brief will illustrate how the analytical pockets at Dell Services transitioned
from a Functionalii
model, as shown in the figure below, to their optimal organizational
structure as a Center of Excellence.
Organizational Structures for Analytics
While there were technological efforts supporting this growth into a cooperative unit, this brief
will focus on the strategic, non-technical approaches that were key to Dell Services’ journey
toward analytical maturity.

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About Dell
Dell Inc. is an approximately $57B company, founded in 1984 and headquartered in Round
Rock, Texas. It provides integrated technology solutions in the IT industry worldwide. It designs,
develops, manufactures, markets, sells, and supports mobility and desktop products; servers
and networking products; and storage products.
Dell Services is a $9B business within Dell Inc. It employs about 45,000 people (40% of the Dell
workforce) and accounts for about 15% of sales. Dell Services offers financial services including
originating, collecting, and servicing customer receivables. It also provides support and
deployment services; infrastructure, cloud, and security services; and applications and business
process services, as well as certain software-related services.
Context
Dell Services has had a strong, lean, Six Sigma culture for many years. In light of this, they had
been viewing processes historically and leveraging them extensively for master data
management implementation. Much of their architecture already included standard enterprise
BI and analytics tools such as SAS and Business Objects. The tools were available and useful to
various decentralized analytics teams, but when the needs of the organization began to evolve
and the lines of business requested the capability to perform ‘what if’ scenarios on the fly, the
Dell Services analytics team recognized that the company’s IT investments and assets were not
being optimally utilized.
Within Dell Services, there is a large population of information workers with job titles like
‘analyst’ or ‘consultant’ that would be enabled by the capability to access ‘on the fly’ analytical
insights. The graphs below illustrate the demographics of the community of potential users –
the knowledge workers.

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Information worker Opportunity by Function
Global Information Worker Opportunity

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There were four main reasons Dell was not operating optimally; each issue pointed back to a
lack of collaboration within the Functional structure of the teams. First, the talent itself was
disparate and disconnected. This presented multiple issues including the inability to share and
learn from one another, as well as the underutilization of many tools since some knowledge
workers didn’t know what was available to them or how to leverage it.
Second, they didn’t have the ability to access multiple data sources and build out insights
leveraging cross-functional data. Third, they weren’t leveraging data visualization to its full
potential - this was an area where many individuals struggled. Finally, to extract the most value
from new tool sets, the Dell team wanted to create an environment where any subject matter
expert interested in analytics and BI could leverage Dell’s IT investments. As mentioned
previously, the capability didn’t exist for an information worker to perform what-if scenarios;
for example, the finance and HR teams couldn’t analyze the impact of staffing decisions on
employee morale or product quality. If one analytics team prepared to select the right tools to
enable their information workers to perform these scenarios, the rest of the organization would
never hear of, or benefit from, their work.
A Business Approach to Community Building
As Dell thought through how they could coordinate and align the analytics teams within Dell
Services, they realized they were building something like a start-up organization within a
corporation. They wanted to take a strategic approach, so they organized their efforts in four
areas: gathering external input, defining the vision, community building, and marketing and
branding.
Gathering Input
Since other major organizations had undergone similar efforts to create their own analytics
teams, Dell sought out leaders at peer organizations to help inform the vision for the ideal
analytics structure and collaborative model at Dell Services. Led by Robert Ayala, Finance Sr.
Consultant, they reached out to Fannie Mae, BMC Software, and BioWare (a gaming company
owned by Electronic Arts), among others. Robert probed for where these peers were in the
process of forming and maturing their teams, their strategy for master data management,
whether they had a data warehouse, and what organizational models they’d deployed and why.
A significant takeaway from these conversations was that while the end result of the analytics
performed by various teams may differ significantly, the in-between processes were very

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similar. For example, some analysts focused on report creation while others focused on
analytical platforms with bigger data that required an agile approach, but there were many
commonalities in their work. These commonalities could be leveraged to gain numerous
efficiencies.
Another benefit came from understanding how analytics provided key insights and value to
these peer companies. For example, BioWare was examining data to determine when gamers
stopped playing, and those results were influencing game enhancements to keep players
engaged. Dell would keep these insights in mind for future collaborative, cross-team meetings.
Each peer conversation also informed the thinking around architectural and organizational
structure. After evaluating the possibilities, Dell decided a Center of Excellence structure would
best meet their needs and goals. Robert indicated, “The analytics teams needed to be close to
their businesses, but that there were clear benefits to collaboration.”
Dell also gathered input internally. The CIO had recently formed a team to conduct an
assessment of their movement along the BI maturity curve. The study incorporated input
throughout IT, from the reporting teams, data scientists and subject matter experts throughout
the business. Analytics team members provided input and remained tied into this network of
BI practitioners, gaining valuable insight about the existing Dell architecture and the strategic
objectives that IT was driving. They were also able to get a better idea of what other groups
within the broader enterprise were doing to execute similar objectives. These relationships
would prove invaluable to the analytics initiative because it refined their objectives and
provided credible feedback from known thought-leaders within the company. In addition, this
community would serve as future champions for analytics efforts.
Community Building
Dell knew that the analytics community would need encouragement to embrace the new
collaboration initiative. To help foster a sense of community, they established the Services
Worldwide Analytics Team (SWAT), including analysts from Finance, Marketing, Human

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Resources, Delivery and more. As Robert had worked at Dell more than 15 years, he knew the
“data jockeys” across the organization and targeted those individuals for engagement first. If
those key people found the experience valuable, they would stay involved and invite
colleagues. A large group of analysts that had been, in some ways, secretive about their
processes and unaccustomed to sharing were also contacted.
Next, Dell created a “Chatter” group for this community using the social media capability
offered by Salesforce. This capability was used extensively in the early stages to facilitate
virtual communication with Dell’s global locations like Bangalore and Slovakia. Finally, they
organized in-person meetings with a “show and tell” approach, inviting all analysts and
everyone involved with analytics, including IT counterparts from infrastructure, data
warehouse, and governance roles. These were monthly, two-hour sessions, with an agenda
often informed by the Chatter communications.
With so many different roles represented, the community quickly recognized that as
individuals, they held unique pieces of role-related knowledge, but no one had a holistic
understanding of an initiative like master data management. When a business analyst shared
how they utilized their tools, the data warehouse and governance team members got a deeper
understanding for whether those tools were truly valuable, or could be modified or replaced to
deliver greater value.
Clarifying the Vision and Value
As the value of this increasingly integrated community became clearer, the Dell team began to
consider how they could influence continued learning and evolution along the analytics
maturity curve. They found that certain people had incredible analytical capability but lacked
data management skills. Others had great infrastructure and tools but hadn’t fully leveraged
their analytical potential. Dell knew these pockets of strengths and weaknesses could be
smoothed out by developing a standardized curriculum for continued education.
Encouraging individuals to participate in these courses was one of the more difficult
recruitment activities, but those who did participate saw accelerated learning curves. Dell
organized training around a variety of topics including data visualization (including thinking by
leaders like Edward Tufte and Stephen Few), data governance, master data management and
specific analytical techniques.
These classes were often customized and leverage analysts’ real data sets. Outside of the U.S.,
they would blend a virtual training with an onsite experience. While every effort was made to
put a scalable course curriculum in place, exceptions were made for when some part of the

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organization expressed specific interest. At times, Dell called in vendors to address an issue, or
peer companies like BioWare to share how they were realizing value from analytics.
Marketing and Branding Efforts
While the Center of Excellence structure came together, Dell also realized that due to the
breadth of involved stakeholders, it was essential to communicate a consistent message about
the newly formed group and its capabilities. They would need to tailor that communication for
their various audiences of IT professionals and business analysts, as well as business leaders.
Through a series of road shows, Robert and the Dell team specifically targeted the larger IT
community in order to demonstrate that they were not violating IT security or governance
protocol. They also looked for feedback to ensure they had accurately planned for IT
complexities. In addition, they opened their training courses to IT attendees as yet another
communication and collaboration opportunity.
In addition to the IT community, Dell also presented prototypes to key business stakeholders
illustrating the analytical capabilities that had been created. For example, they would meet
with an HR information worker and pull up their data, then show them how it could be
manipulated with agile tools. Recognizing that unsolicited input is not always welcome input,
the analytics team would present the available tools and demonstrate how they could be
applied by the end user. They made certain to communicate that the analytics team was
specifically providing the capability, but the credit for the results would belong to the
information workers.
For the most important and influential stakeholders, Dell would set up one-on-one meetings to
communicate about the analytics teams’ capabilities or their notable successes.
Conclusion
Qualitative results
The cross-functional collaboration that is taking place continues to yield unexpected results.
Teams have begun sharing data sources, visualizations and even analytical techniques. As a
result, Dell has begun to see “white space” analysis on non-marketing data sets and mash-ups
of HR and financial data that can be used to create role-based performance indicators. These

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indicators will align with corporate strategies and allow for the most efficient allocation of
company resources.
The new model has also benefited employee morale for this previously unorganized
community. The complexity in capturing, managing, and massaging the data into something
insightful is a difficult and cumbersome job - those that immersed themselves in the details of
the data were rewarded for their patience as now, they drive a disproportionate amount of the
value from analytics within their organizations. It has solidified their seat at the decision-
making table and opened up new career paths.
Quantitative results
One global team in the Dell Services organization tasked a summer intern with tapping into
massive amounts of data around the online support environment. Previously, this kind of
analysis could not have been delegated to an intern. The ramp time for learning the business,
finding and managing the data, and the data mining and discovery process would have been
too extensive. No supportive ecosystem was in place to enable the intern.
In the new collaborative structure, within a matter of weeks and supported by a community of
practitioners and an IT managed infrastructure in place, the intern returned impressive findings.
These conclusions resulted in $6.1M projected savings associated with fewer customer touch
points, improved content navigation, and better server/network capacities. This dollar amount
does not yet include the cost benefit from the reduction in abandon rates and potential future
revenue streams from the improved overall customer experience. Along with the dollars saved,
the roadmap cycle time was also significantly accelerated.
Several years ago, a Hackett benchmarking study on Robert Ayala’s finance organization at Dell
Services indicated that financial analysts were spending 70% of their time collecting data and
only 30% of their time analyzing it. Very likely, most of that 30% of time spent on ‘analysis’ was
consumed with data presentation, rather than true analysis. Because the new collaborative
environment had specifically targeted the development of data visualization skills and forged
stronger partnerships with IT to make data more easily accessible, the Dell Services team has
reversed those ratios. In the future, they aim for more than 95% analysis and less than 5% data
collection.
The Future
Dell’s structure is now primarily a Center of Excellence, incorporating a network of spokes that
make the topography look like a spider web. This is partially a reflection of the similarity in data

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needs across teams, but is also a reflection of the data mash-ups and collaboration taking place
as a result of this new environment.
The team’s plan is to continue to nurture and build out this community of practitioners across
all functional areas to ensure they are potentiating people and infrastructure investments. The
competition for good talent is intense and if Dell can maintain an environment that attracts,
cultivates, and retains good analytical talent, they can increase their likelihood of success as an
organization. It will enable them to leverage fact-based knowledge to drive innovation,
efficiency, productivity and profitability throughout their business.
Dell has also started working with their product development and customer facing teams to
provide feedback on solutions that help their customers be successful in their own business
intelligence and analytics implementations. Lastly, while other projects compete for executive
mindshare, Dell will continue to champion the need for analytical capability and innovation in
their organization.
i
Thomas H. Davenport, Jeanne G. Harris and Robert Morison, Analytics at Work: Smarter Decisions, Better Results, Harvard
Business Press, 2010.
ii
Thomas H. Davenport, Jeanne G. Harris and Robert Morison, Analytics at Work: Smarter Decisions, Better Results, Harvard
Business Press, 2010. Also see IIA’s Organizing Analysts: Parts 1 & 2 for more in-depth information.

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