the information-driven enterprise

A Forrester Consulting Thought Leadership Paper Commissioned By Hewlett-Packard

The Information-Driven Enterprise

Businesses Are Increasingly Driven By Analytics, But Disconnects Can Sabotage The Best Intentions

November 2012

Forrester Consulting


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Table Of Contents

Executive Summary ................................................................................................................................................................................. 2

Businesses Have Big Plans For Data..................................................................................................................................................... 3

Localized Approaches Miss Enterprise Synergy ................................................................................................................................ 5

A Unified Approach Unlocks More Value ......................................................................................................................................... 7

Key Recommendations ......................................................................................................................................................................... 10

Appendix A: Methodology................................................................................................................................................................... 11

Appendix B: Demographics ................................................................................................................................................................. 11

Appendix C: Endnotes .......................................................................................................................................................................... 12

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Eight in 10 executives are planning to use more

data for analytics in the next 12 months, with one

in three planning for a substantial increase in

data volume, data velocity, or the types of analytics performed.

Executive Summary

Information is emerging as the new currency of business as well as the basis for

true differentiation and value creation. However, traditional disconnected

information management approaches limit potential. In June 2012, Hewlett-

Packard (HP) commissioned Forrester Consulting to study how firms were

progressing in the quest to become information-driven. We believe that

businesses are pursuing analytics using more data and new tools because these

lead to both efficiency and new business opportunities. However, obstacles exist.

To test this assertion, we conducted a survey of 154 business technology

executives and interviewed four North American companies in the financial services, business-to-consumer,

manufacturing, and agriculture verticals. We found that while firms are generally looking to data for more insight,

organizational misalignments, lack of trust, and talent gaps are significant issues that firms must overcome by 1)

aligning business and IT objectives; 2) investing in systems that can integrate structured and unstructured data in a

scalable, cost-effective manner; and 3) creating partnerships to fill critical talent gaps.

Key Findings Forrester’s study yielded five key findings:

• Businesses are letting data guide their strategic decisions. Seventy-six percent of firms we surveyed believed

that digital data was critical to their business. Our interviews reinforced this by revealing business leaders who

were focused on improving the quality and quantity of data available for decision support. We found firms

combing through data looking for insight and using that insight to act rapidly and prepare for market shifts. In

order to become data-driven, firms must overcome important cultural issues, starting at the very top.

• Disconnects and misalignments inhibit enterprise benefits. Fifty percent of firms stated that their data policy

was to treat it as a corporate asset, but only 38% of firms said that actual behaviors reflected this. Furthermore, we

found differences between how IT and business respondents view big data opportunities. These are examples of

misaligned objectives that result in slow progress. Firms must take a hard look at how IT and the business are

incentivized to work together toward common business goals.

• Big data will play a significant role in lowering the cost of data at extremes of scale. Our study probed the role

that advanced analytics and big data solutions will play in enterprises. Sixty-two percent of respondents believe

that big data will lower costs; the top use cases involved integrating structured and unstructured information.

Firms expect cost to be lower because 1) big data solutions are more cost-effective at integrating highly diverse

data sets at extreme scale; 2) big data solutions are scalable, allowing firms to acquire only what they need; and 3)

big data technology costs are being pressured downward by open source.

• Trust is an issue that context helps overcome. Eighty-five percent of respondents said that trusting the analysis

of advanced analytics was a critical or significant challenge for them. Seventy-nine percent said that trusting the

data was an issue as well. Trusting the data and analysis requires building on experience, which can be difficult to

acquire. Firms can get a jump-start by using various unstructured, human-generated sources to provide context

in number-crunching analytics. For example, one executive told us about a social media analysis that confirmed a

predicted influx of new business.



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• Talent gaps are widening with big data. While firms generally believed that they had or could hire sufficient

talent, gaps were identified. Only 13% believed that they had sufficient data science talent, and only 22% believed

that they had the personnel to deliver big data solutions. Firms are leveraging centers of excellence (CoEs) to

leverage limited talent. Additionally, interviewed executives confirmed that partners were helpful in getting up to

speed with big data. However, they also warned us to be careful. Firms must select partners that understand the

business need and data, not just the technology.

Businesses Have Big Plans For Data

Fueled by the increasing competition and the relentless commoditization of products and services, firms are actively

looking for new revenue opportunities (see Figure 1). Our study found firms turning to advanced analytics as part of

their strategy to identify new business opportunities, deepen customer engagement, and become more efficient.

Specifically, we found that:

• Firms view data as critical, not just important. In our study, we asked firms to tell us about their data

management philosophy and found that 76% thought that data was critical to their business, while the remainder

thought that it was just important (see Figure 2). Moreover, our interviews backed this up.

“Data has given us a strong competitive advantage — we are a lot smarter than our competition because we are

much more nimble and able to test out what might work and find out what does not.” (Director of eMarketing,

consumer rental company)

“We have a lot of information on our product, but buyers are not confident. To get our new products adopted in

the market faster, we turned to advanced analytics to improve confidence and shorten sales cycles.” (Business IT

systems lead, agricultural firm)

• Leaders are becoming more dependent on real-time data. The executives we spoke with reflected a common

theme — transforming their organizations by using more comprehensive and real-time data sets for effective

decision-making.

“We are very much setting our strategy based on market data. We have planning processes, and the amount of

data provided to those processes by our analytics team is mind-boggling . . . . We have hugely benefited from

competing on analytics.” (Vice president of applied analytics, US-based insurance company)

“We are always looking at data to optimize our strategies . . . . We dig through data in our [tool] and look for

patterns across the market.” (Director of eMarketing, consumer rental company)

• The top use cases involve a variety of structured and unstructured data. We asked our survey participants

about how they planned to use big data as part of their overall strategy to become information-driven (see Figure

3). The top new use cases required the most diverse data sets including a significant amount of unstructured data

— these included market microsegmentation, customer next-best action, and sentiment analysis. Furthermore,

quick and dirty is often preferred over precise and expensive when conducting analysis.

“[People are] being forced to realize that things are a bit dirtier in the real world. Good enough may be good

enough for some things.” (Business IT systems lead, agricultural firm)



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• Firms are turning to big data for lower costs and improved efficiency. Sixty-two percent of our survey

respondents indicated that they expected big data technologies to have lower costs. We believe this is because 1)

traditional extract-transform-load-based systems cannot effectively deal with a wide variety of different formats

at extremes of volume and velocity; 2) big data solutions can scale, so firms can buy only what they need; and 3)

open source alternatives are exerting downward cost pressure.

Figure 1

Firms Are Actively Looking For New Revenue Opportunities

Base: 154 IT and business professionals involved in data analytics decisions

Source: A commissioned study conducted by Forrester Consulting on behalf of HP, June 2012

Figure 2

Data Is A Critical Component Of Firm’s Plans





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Figure 3

New Big Data Use Cases Require Diverse Data


Source: A commissioned study conducted by Forrester Consulting on behalf of HP, June 2012 Note: Respondents who answered “no plans” and “don’t know” were not included.

Localized Approaches Miss Enterprise Synergy

Becoming information-driven means having an enterprise view and being able to act on data both tactically and

strategically across machine, human, and sensor data.

“It’s hard to predict how folks are going to need information; you can see it at a strategic and tactical level.”

(Global manufacturing manager, manufacturing company)

Our study revealed organizational issues that can defeat the best intentions. For example:

• Disconnects exist between what firms say and what they do. Fifty percent of respondents indicated that their

firms’ data management philosophy is managing data like a corporate asset, but only 38% said that people in their

firms actually behaved that way (see Figure 4). This is because firms are trying to be information-driven, but they

use data in an intuitive, subjective manner that under-delivers on insight.

• IT is too narrowly focused on data that it can most easily access. In our survey, we asked respondents about the

types of data on which they plan to use big data analytics (see Figure 5). The results indicate that IT focused more

on structured data available from internal systems, while business people’s interests were more evenly distributed.

We think that one of the primary benefits of big data is the integration of structured transactional data and



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unstructured, human-generated data, and our interviews confirmed our point of view. This narrow IT view can

lead to missed value.

• Frustration exists with and within IT. IT is often frustrated because it has a view into data at an enterprise level

and often takes the brunt of blame when solutions take too long or cost too much. The business executives we

interviewed reinforced our assessment.

“We try to avoid IT projects if at all possible. It is very painful and we don’t like it.” (Director of eMarketing,

consumer rental company)

“The problem with most IT systems is they assume that nothing ever changes, but the manufacturing process is

all about constant change to optimize and become more efficient.” (Global manufacturing manager,

manufacturing company)

These issues result in distrust that further fuels division, when working together will yield the best results.

Figure 4

What Firms Say About Data And What They Do Are Different





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Figure 5

IT Is Focusing On Internal, Transactional, And Structured Data

Base: IT and business professionals involved in data analytics decisions in each role


A Unified Approach Unlocks More Value

Enterprise information management has been a concept for years. However, it is often driven by IT because IT deals

with data at an enterprise level every day.1 Businesses, on the other hand, are disillusioned. For example, our survey

revealed that 62% of business respondents thought that funding for big data solutions that required new technology was

an inhibitor to their analytic strategy, while only 18% of IT respondents thought this. This huge difference underscores

the basic problem — businesses are tired of spending money on new technology when IT is involved.

Overcoming disconnects and misalignments will unlock more value through:

• Sharing information and insights to empower your business. One executive stated the problem clearly.

“Our biggest challenge is being able to share data across the organization. For example, if somebody at one plant

has a good idea, how do we ensure that everyone benefits?” (Global manufacturing manager, an equipment

manufacturing company)



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One company we interviewed had it figured out. It used social media monitoring and sentiment analysis to

complement hard data in developing sales forecasts. Because it could share insights easily, it could react very

quickly to market changes.

• Holistically addressing more than cost savings with big data solutions. Both business and IT respondents in

our survey agreed that cost savings was the No. 1 driver for investigating big data. However, IT is also concerned

about volume, velocity, variety, and variability issues (see Figure 6). For example, the figure illustrates that 42% of

IT respondents were looking at big data solutions to address high-volume problems, while only 23% of business

respondents said the same.

• Providing context that improves data trust. Our survey indicated that trust was a particular concern with

advanced analytic solutions. Eighty-five percent of respondents said that trusting the analysis was a critical or

significant challenge for them. Also, 79% said that trusting the data was an issue. We believe that trust is

improved when context from various human-generated, unstructured sources can be combined with hard

number-crunching analytics. One executive we interviewed reinforced this point.

“The key to understanding the insights is having the context; you need to look across channels to understand

what the customer is doing.” (Director of eMarketing, consumer rental company)

• Creating analytics CoEs to leverage talent. In our survey, 53% of firms indicated that they either have or plan to

have a data analytics CoE to centralize talent, while 31% employ or plan to employ a hybrid model with both

central and line-of-business teams (see Figure 7). We think that this is logical given that 85% of respondents told

us that gaps exist in the quantitative data analyst/scientist role.

• Building an ecosystem of partners to accelerate time-to-value. Our survey indicated that talent gaps were a

significant issue to realizing value from more data. Only 13% believed that they had sufficient data science talent,

and only 22% believed that they had the personnel to deliver big data solutions. For both of these gaps, our survey

also revealed that firms were most likely to look to partners. Several executives who had leveraged partners

reinforced the important of finding the right one.

“Having a trusted partner is very important to achieving our vision . . . . Those who try to adapt your problem to

their solution du jour aren’t helpful.” (Global manufacturing manager, equipment manufacturing company)

“We haven’t played in this data space before. Having a partner has been critical, but you need to understand

what’s real and who’s not.” (Business IT systems lead, agricultural firm)



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Figure 6

Everybody Cares About Cost, But IT Also Sees Volume, Velocity, And Variety Benefits

Base: IT and business professionals involved in data analytics decisions in each role

(multiple responses accepted)


Figure 7

Firms Leverage Analytics Talent By Creating CoEs





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KEY RECOMMENDATIONS

Key recommendations for organizations on the path to becoming information-driven, based on the findings of our study,

include the following:

• Start with your culture. One executive put it poetically, “Success with data means changing hearts and minds

of your people.” We see this over and over again in our research. Effective data management begins with

organizational culture, and big data is no different. If the CxO level is not thinking “information-driven,” all of

the big data technology in the world will not help. In this case, work tactically to prove the value in small

chunks with the aim of influencing a change in attitudes.

• Stay focused on business problems. One of our interviewees told us, “I’ve never seen a better partnership

between the business and IT. Our IT team is really focused on the business objectives, not focused on [its] own

agenda by doing all kinds of things that only [IT is] interested in.” Realigning IT with business objectives for an

information-driven enterprise is critical and starts at the top. Ask yourself, why is IT doing what it’s doing? What

business problems are being solved?

• Make enterprise analytics a team effort, but let your business lead. Funding new technology for big data

investments is a difficult issue for business due to eroded relationships, and most firms in our survey plan to

establish an analytics CoE and leverage line-of-business teams. Clearly IT has a role to play in supporting a big

data and an advanced analytics infrastructure. However, we think that the bulk of the analytics workload

should be put in the hands of business teams. Giving the business control will rebuild trust and establish IT’s

position as an enabler and not an inhibitor.

• Use human-generated data to add context. IT’s top interest for big data lies in improved processing of

transactional data at extremes of scale. However, business is also interested in human-generated data such as

unstructured scientific and social. We believe that the best solution integrates these data sets to provide a

contextual overlay to deep analytics insights that will improve trust. Since integrating extreme-scale,

multisource data to provide both context and insight requires hard-to-find skills, create relationships with

partners that have experience in both the breadth of technology and your particular industry.



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Appendix A: Methodology

In this study, Forrester conducted an online survey of 154 IT and business professionals involved in data analytics

decisions for their organizations to better understand the needs and perceptions of big data in the enterprise. Responses

were collected across a broad range of industries and across four countries. Forrester also conducted four follow-up

interviews with decision-makers who responded to the survey. In both the online survey and follow-up interviews,

respondents were asked a series of questions about their organizations’ current practices and challenges concerning

data management as well as the analytics tools and solutions in use or planned for use in the future. The study began

and was completed in June 2012.

Appendix B: Demographics

Figure 8

Organizations By Headquarters Location And Number Of Employees


(percentages may not total 100 because of rounding)




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Figure 9

Organizations By Industry



Appendix C: Endnotes

1 According to Forrester’s 2011 MDM survey, 36% of firms have IT-driven enterprise data governance efforts, while

44% have a low all-around maturity. Source: August 2011 Global Employee Master Data Management Online Survey.

the information-driven enterprise

Technology

hewlett data

unstructured data

digital data

data policy

business leaders

percent of firms

big data opportunities

forrester wave