Survey Results Age Of Unbounded Data June 03 10

Leading in

The Age of Unbounded DataSurvey Results, 2010

IntroductionWelcome to the age of unbounded data

2 | © 2010 nGenera Corp. All Rights Reserved.

Leading in the Age of Unbounded DataEnter the highly-instrumented enterprise


Enterprises Have Become Highly-Instrumented;

Using new sources of data combined with sophisticated analytics to

distinguish signal from noise, create better situational awareness, drive

new insights, and uncover the ROI of collaborative initiatives.

Leading in the Age of Unbounded DataIt’s not just that we have more data…


More data Over 50% of respondents ‘agree’ or ‘strongly agree’ that more data leads to better

decision making, but 46% spend more time looking for information today than before.

More data from new and expanding sourcesAlmost 60% of respondents report an increase in the number of data sources used for decision-making in

the past 12 months; two-thirds of companies believe managing data from new sources is an important issue.

More interactions among data types and between people and data70% of respondents ‘agree’ or ‘strongly agree’ that executives who have

more varied types of data will improve the quality of their decisions.

Growing availability of open dataOver 70% of companies say that deciding how much data to open or share

is either an ‘important’ or ‘very important’ issue.

Making sense of this data ecosystem is the fundamental challenge facing enterprise decision-makers, analysts, and IT departmentsDespite the glut of available data, only 33% of respondents indicated that

they have the data they need to do their jobs.

Leading in the Age of Unbounded Data…enterprises must make sense of the data ecosystem


Sense-making trumps all other data prioritiesImproving the ability to interpret data (and get it to senior executives) is the

number one data priority; far more important than getting access to more data.

Data quality is a bigger problem than data availability‘Data integrity and quality’ is the number one data problem vexing survey respondents; deemed to be a far greater issue than ‘data availability.’ The use of unstructured data in

measurement is a significant contributor to quality issues.

Focusing on customer data will be a competitive priorityData from customers will drive competitive advantage, but currently data quality is low and

sharing of information back to customers (i.e. creating a two-way value proposition) is a low priority.

Both new data and legacy data are causing problemsManaging legacy data is proving almost as hard as managing data from new channels

(rated as ‘very important’ by 32% and 34% of respondents respectively).

Companies still lag when it comes to measurementOnly 23% of respondents are measuring the ROI of collaborative initiatives; just over half are measuring

employee productivity. In both cases, fewer than 40% report ‘good’ or ‘excellent’ quality data.

Leading in the Age of UnboundedSurvey methodology

• Survey results gathered from January 15th to March 1st 2010.

• Responses from over 70 major organizations, including several state/provincial governments and many global corporations.

• Majority of respondents are director-level or higher executives from within various functions.


23%

16%

13%

9%

5%

5%

5%

4%

4%

4%

3%

3%

6%

0% 10% 20% 30%

Consulting

Software/Technology

Government

Finance/Banking

Medical/Healthcare

Retail/Consumer Products

Advertising/PR

Transportation

Education/Training

Telecomunications

Publishing

Utilities

Other

16%

19%

30%

35%

Staff

Manager

Director

Senior/Executive Management

nGenera Data SurveyData-driven competitive advantage


Survey Overview: Data-Driven Competitive AdvantageExternal data is a key driver of competitive advantage

88% of respondents say that data drives competitive advantage.Collaboration around data is an important part of seizing the opportunity. While internally created data and data gleaned from user and customer interactions are still seen as most important, increasingly data from

outside the enterprise is also driving competitive advantage. Data created with customers and partners, data acquired from third parties, and open data are all considered integral contributors to competitive strategies.


77%

68%

49%

44%

43%

22%

12%

0% 20% 40% 60% 80% 100%

From customer and user interactions

Internally created

Co-created with customers

Co-created with business partners

Acquired from external parties

Open data

Other

Competitive advantage is not data-driven

What sources of data drive competitive advantage in your organization?


Survey Overview: Data-Driven Competitive AdvantageMost pronounced worry among decision makers is data integrity and quality

How important are the following problems related to enterprise data?

73%

56%

53%

53%

39%

39%

36%

34%

9%

18%

31%

30%

26%

32%

32%

32%

27%

6%

0% 20% 40% 60% 80% 100%

Data integrity & quality

Timeliness of data

Data availability

Data security

Managing data rights

Deciding how much data to open or share

Managing data from new channels

Managing legacy data

Other

Very Important Important

More data improves decision-making, metrics, and agility, but also creates complexity and more noise in the system. Some critical issues include availability and timeliness of data for decision-making, data security and

access rights, and deciding how to share data and with whom.

Survey Overview: Data-Driven Competitive Advantage Across data types, fewer than half rate the quality of data as ‘good’ or ‘excellent’


The low quality of customer data is particularly worrying (only 27% say it is ‘good’ or excellent’), as this data was

seen as a key driver of competitive advantage.

Fortunately, many new tools and technologies are emerging to help address this, including

‘voice-of-the-customer’ listening platforms and

sentiment analysis tools, as well as prosumer platforms

that harness customer insight and ideas, and next-generation

social CRM solutions that promise to integrate data from social media interactions into

customer databases.

Rate the quality of data for day-to-day decision making

47%

42%

29%

27%

17%

27%

25%

26%

27%

32%

23%

23%

40%

34%

35%

0% 20% 40% 60% 80% 100%

Function-specific data

Employee data

Enterprise data (cross-function)

Customer data

Partner and supplier data

Good/Excellent Average Below Average/Poor


Survey Overview: Data-Driven Competitive Advantage Sense-making is paramount in a world of abundant information

What are the data priorities for your organization?(percentages shown are based on respondents rating priorities as ‘high’ or ‘very high’) Sharing data is still not huge

priority, but we believe that it’s going to have to be given the growing importance of

data ecosystems. In order to fully leverage opportunities

related to customer data and data from external partners,

companies will need to share their own information

and create two-way value propositions. The lack of priority being placed on sharing and measuring

return points towards a real opportunity for leading

organizations to redefine competitive advantage.

79%

75%

74%

70%

69%

62%

61%

61%

58%

52%

43%

40%

34%

0% 20% 40% 60% 80% 100%

Getting data to senior executives more quickly

Improving our ability to interpret data

Improving data quality

Getting more timely data

Measuring customer experience

Getting data to front line employees more quickly

Sharing data with employees

Managing unstructured data

Getting access to more data

Measuring return on collaborative initiatives

Managing data from social media

Sharing data with customers

Sharing data with external partners

Data and the Ability to MeasureWhat was previously unknown can now be known


Data and the Ability to MeasureWhat are companies measuring?


The Age of Unbounded Data is a result of a dramatic increase in the amount of sensor technology, web analytics, document tracking, and other instrumentation that is now commonplace in our homes, organizations, and public places. The influx of more and different types of data provides organizations with an unprecedented

opportunity to improve what and how they measure and report.

23%

65%

53%

ROI of collaborative initiatives

Customer experience

Employee productivity

Which of the following do you measure?


Data and the Ability to MeasureThe ROI of collaborative initiatives

Today, only 23% of respondents are measuring the impact of collaborative initiatives.

• Among those that are having success, most are using a combination of analytics and proprietary techniques.

• As workflows are increasingly digitized, process mining will uncover new types of ROI metrics for tasks and initiatives that were previously qualitatively measured (if at all) due to their unstructured nature.

• Over half of companies say that measuring ROI of collaborative initiatives is a high priority. Given how important it is, we expect the number of organizations measuring ROI to increase significantly over the next 12-24 months.

• nGenera’s research has shown that measuring ROI depends on identifying an intent for the collaborative initiative that is tied to a specific business outcome—why are you collaborating and what type of collaboration are you going to use?


Data and the Ability to MeasureCustomer experience

65% of survey respondents actively measure customer experience.

• There isn’t a huge difference in the type of methods used by those having success in this area and those struggling—the vast majority use customer surveys and feedback forms—indicating that the major issue for companies with customer experience measures may be the questions being asked and the processes surrounding customer feedback rather than the data-gathering methods.

• By systematically gathering and analyzing customer anecdotes (e.g., using social media monitoring and text mining), companies can augment survey measures and satisfaction scores with more story-driven measures of experience.

• Just about any organization can listen to and leverage the stories of average people that write online in blogs, forums, Twitter, and social networks every day.

• There are effective new methods for collecting and analyzing customer data that are not yet widely used including social media monitoring tools, listening platforms, text analysis, and customer sentiment analysis.


Data and the Ability to MeasureEmployee productivity

A little over half (53%) of respondents are actively measuring employee productivity.

• The leading types of measurement used are a combination of time tracking, performance management software, and 360-degree peer reviews.

• New sources of data can create visibility into poorly-understood informal networks and allow organizations to redirect their attention towards what’s going on ‘below the surface’ of established structures.

• Software is now available that can track e-mail messages, shared documents, calendar information, call logs, and contact information to model collaborative behaviour and map informal lines of communication.

• By mining employee processes, companies can target key influencers, find new efficiencies, strengthen existing forms of collaboration, and encourage nascent creativity. We can know which employees are producing high-value information, which employees are good curators of information, and which employees may be engaging in harmful activities.


Data and the Ability to MeasureThe role of unstructured data

Unstructured data is playing a significant role in what is being measured. Over 50% of those that measure collaboration, employee productivity, or customer engagement incorporate

some form of unstructured data.

What type of data do you use to measure?

44%

44%

44%

16%

32%

56%

40%

24%

0% 20% 40% 60% 80% 100%

ROI of collaborative initiatives

Customer experience

Employee productivity

Structured Unstructured Both

Data and the Ability to MeasureConsistency of data quality decreases as amount of unstructured data increases

How would you rate the quality of the data used for measurement?

Those using structured data reported higher quality rating than those using unstructured

data. Unstructured data like text, images, audio, and video is hard to organize and

analyze; however, the technologies that allow companies to do so are starting to become

enterprise-grade. Companies that harness tools like text mining, picture and video tagging, and

voice analysis will definitely have an edge in measurement.

17%

38%

23%

42%

38%

48%

42%

24%

30%

0% 20% 40% 60% 80% 100%

Structured

Unstructured

Both

Below Average/Poor Average Good/Excellent


0%

22%

39%

39%

0%

4%

14%

44%

34%

4%

ROI of collaborative initiatives Customer experience Employee productivity

10%

20%

44%

24%

2%Very Poor

Below Average

Average

Good

Excellent

Data Improves DecisionsMore information, more decision-makers, and greater agility


Data Improves DecisionsOver 50% ‘agree’ or ‘strongly agree’ that more data leads to better decisions


26%

26%

27%

16%

5%

Strongly Agree

Agree

Neither Agree nor Disagree

Disagree

Strongly Disagree

The majority of survey respondents agree that more is better when it comes to data. Additionally, 70% ‘agree’ or

‘strongly agree’ that executives who have more varied types of

data (e.g., audio, video, text, statistics) will improve the quality of their decisions.

Yet more data can also lead to more noise and distraction.

There was also a contingent—21% of respondents—that

‘disagreed’ or ‘strongly disagreed’ that more data lead

to better decisions. Clearly, simply having more data is not

a panacea.

To what degree do you agree with the statement “having more data lead to better decisions”?


Data Improves Decisions“If HP knew what HP knows, we would be three times as profitable.”– Former HP CEO Lew Platt

Improving the ability to interpret data is a top priority for companies. A major obstacle is that, in many companies, data still tends to be siloed. Close to 80% of respondents indicate that data sharing is sub-optimal:

44% state that data is siloed by department and 27% state that even when data is shared across departments, it is often inconsistent. Sharing and making sense of data in real-time accomplishes two goals: greater agility

through immediate response and better predictions about the future behavior of people and markets.

What statement most accurately reflects the situation in your organization?

8%

44%

27%

5%

16%

0% 10% 20% 30% 40% 50%

Nobody knows anything

Data tends to be siloed by department

Data is shared but is often inconsistent

There is a single version of the truth accessible to all departments

Data is available for simulation and modeling across the enterprise


Data Improves DecisionsEmerging data opportunities tied to predictive analytics

36%

38%

35%

29%

19%

18%

12%

9%

9%

6%

4%

0% 10% 20% 30% 40% 50%

We do not use predictive analytics

Customer relationship management

Financial modeling

Up-selling or cross-selling

Risk management

Direct marketing

Supply chain or inventory management

Fraud detection

Security threats

Manufacturing or equipment failures

Other

How does your organization use predictive analytic tools?Predictive models can help decision makers

refine business plans in response to unexpected

challenges or opportunities by giving them insight into the

likely outcomes of decisions. Everyday

workers can optimize some of the most

important decisions and signal which initiatives

to launch, accelerate, or stop using ‘what-if’

scenarios that leverage both historical and

current data.


Data Improves DecisionsBeyond local optimization: Leveraging and sharing data enterprise-wide is the goal

While the majority said that certain individuals use data to support decisions, the clear opportunity is in the collaborative and automated spaces. While there is little activity in those areas today—a little over a third using

collaborative data and only 16% using automated decisions—we believe there is a big upside for companies willing to take a leadership position in these areas. Incorporating collaboration and automation into the decision-

making process could bring more effective and faster means of making successful decisions.

69%

60%

33%

27%

16%

9%

0% 20% 40% 60% 80%

Data is used to drive decisions by certain individuals

Data is used to conduct analytics that support decisions

Data is used to drive collaborative decision-making

Data is used to support professional expertise or "gut-feel"

Data is used to automate decision-making

Data is rarely used for decision-making

How is data used for decision-making?


Data Improves DecisionsEnabling ‘everyman analytics’

• With the proliferation of data, we’re also seeing the democratization of analytics. This will have vast implications for the role of the analyst, which will become much more specialized.

• Our survey shows that while analytics is pervasive, it’s not always strategic: 66% of respondents conduct analytics themselves but only 10% have a dedicated analytics group.

• Since we didn’t define “analytics” in the survey, we can assume that the 66% includes everything from ‘Excel warriors’ and power users, to users of free tools such as Google analytics, to more sophisticated business intelligence software.

• 17% are not conducting analytics at all.

10%4%

66%

17%

3%

We have an analytics group

We outsource most of it

We do it ourselves

We do not currently use analytics

Other

How does your department handle its analytic needs?

Data Enables Customer EngagementA clearer view of customers’ behaviours, preferences, and actions


Data Enables Customer EngagementCustomer data is highly valued


Already, data created by customers and users—either indirectly by mining their interactions or directly via co-creation—was ranked very high when respondents were asked to identify which sources of data drive

competitive advantage in their organizations (1st and 3rd respectively). Not surprisingly, almost two-thirds of companies are measuring customer experience (see Slide 15 for details).

77%

68%

49%

44%

43%

22%

12%

0% 20% 40% 60% 80% 100%

From customer and user interactions

Internally created

Co-created with customers

Co-created with business partners

Acquired from external parties

Open data

Other

Competitive advantage is not data-driven

What sources of data drive competitive advantage in your organization?

Data Enables Customer EngagementCustomer priorities are often out-of-synch


While measuring customer experience was rated a ‘high’ or ‘very high’ data priority by 69% of respondents, sharing

data with customers was deemed a priority by only

40% of respondents.

Sharing data with customers is one way of creating a more

valuable customer experience. Organizations

that share data and are transparent will build trust with customers, open the

door for co-innovation, and ultimately gain competitive advantage from customer-

and user-created data.

79%

75%

74%

70%

69%

62%

61%

61%

58%

52%

43%

40%

34%

0% 20% 40% 60% 80% 100%

Getting data to senior executives more quickly

Improving our ability to interpret data

Improving data quality

Getting more timely data

Measuring customer experience

Getting data to front line employees more quickly

Sharing data with employees

Managing unstructured data

Getting access to more data

Measuring return on collaborative initiatives

Managing data from social media

Sharing data with customers

Sharing data with external partners

What are the data priorities for your organization?(percentages shown are based on respondents rating priorities as ‘high’ or ‘very high’)


Data Enables Customer EngagementMany organizations are stuck in a CRM-centric view of customer data

64% of respondents report monitoring social media.Social media data can reveal an individual’s or group’s attitudes towards a brand, a person’s influence within a

target demographic, or an emerging issue in the marketplace. Unfortunately, only 43% of respondents view social media as an ‘important’ or ‘very important’ data priority. We expect to see this channel become more of a

priority as organizations get better at mining and finding value in that data.

36%

39%

30%

29%

27%

22%

18%

0% 10% 20% 30% 40% 50%

We do not collect data from social media

Market research

Brand management

Relationship management

Customer experience management

Hiring and recruiting

Product development

Other

How do you use data collected from social media tools such as social networks, Twitter, blogs, and forums?

Data As a ProductAggregated, anonymized data is a valuable commodity


Data As a ProductFuture opportunities extend beyond enterprise data to data ecosystems


• There is a potential market for data: Over 40% of respondents said data from external sources led to competitive advantage.

• Companies that have social platforms are increasingly seeing a business model around providing free services and aggregating anonymized customer and user data for sale. This user data is being leveraged in many ways, with 77% indicating that data from customer and user interactions are a source of competitive advantage.

• 71% of respondents said deciding how much data to open and share is ‘important’ or ‘very important,’ but sharing of data with external partners and customers was rated as a relatively low priority (last and second-last respectively on a list of 13 data priorities).


‘Open IP,’ where companies and institutions add to the data commons, is an emerging, if somewhat immature trend. Currently only 30% of respondents have open data identified as an important part of their strategy; 31% have not yet considered a strategy for open data. Discouragingly, 17% of respondents say they have considered

but rejected an open data strategy.

Data As a ProductOpen data initiatives are still immature

31%

30%

17%

22%

0% 10% 20% 30% 40% 50%

An open data strategy has not yet been considered

Open data is an important part of our future growth strategy

Open data has been considered and is not on our current strategy agenda

Our open data strategy is still being debated

What is the organization’s open data strategy?

Key TakeawaysUncover new opportunities and unleash hidden potential


Key TakeawaysLeading in an age of unbounded data requires new thinking


Leading in an Age of Unbounded Data is Not Just About Having More Data, but also about

how we manage interactions among data types and

interactions between people and data, our ability to

interpret data and find meaning, and the extent to

which we embrace data sharing and open data

strategies. Decision-Makers Must Understand the Data Ecosystem.

Key TakeawaysLeading in an age of unbounded data requires new thinking


Key learnings from the project include:

• Data is a critical enabler of the next generation enterprise.

• The data revolution is not just about more data.

• Future opportunities extend beyond enterprise data to data ecosystems.

• Digitizing processes will lead to new types of measurement and optimization.

• Customer data is a leading contributor to competitive advantage.

• More types of data lead to better decision making.

• Sense-making is paramount; the most successful companies compete on analytics.

• Aggregated, anonymized data is a good way to monetize interactions.

Key TakeawaysLow hanging fruit: Opportunities for leading enterprises


We believe they are several elements of data strategy that are critical to driving the next generation enterprise, but that are still nascent. The lack of activity in the following areas reveals an opportunity for leading organizations:

• Leverage tools to get high-quality customer data – Although customer data is identified as a key driver of competitive advantage, few companies are currently getting data that is of high quality. New tools such as ‘voice-of-the-customer’ software, listening platforms, prosumer platforms, and sentiment analysis tools, as well as emerging social CRM offerings, will help close this gap.

• Share data – Companies that open and share their data will reap the benefits of an ecosystem of customers, partners, and employees. Sharing data with customer creates a two-way value proposition and generates new opportunities for co-innovation. Sharing data internally improves analytic capabilities , customer responsiveness, executive visibility, and overall agility.

• Measure ROI – Over 50% of companies say that measuring the ROI of collaboration is a high priority, yet only 23% actually do so. Part of the problem is the difficulty related identifying metrics. Still, companies that have success in this area will be able to optimize collaboration and improve productivity.

Key TakeawaysLow hanging fruit: Opportunities for leading enterprises


• Focus on social media – Customers are focused on social media, and companies should be too. Communicating via social media can lower costs and data gathered from social media channels can not only lead to new insights, it can even generate new revenue when anonymized and packaged for interested third parties.

• Prepare the enterprise for analytics – The most successful organizations compete on analytics. Data analytics leads to better data interpretation and sense-making. Companies that are really good at analytics are also good at gathering data, sharing data, and consolidating it to get a ‘single version of the truth’ across the enterprise.

• Support decision-making with automation and collaboration – Few companies are currently looking to decision-automation or collaborative decision-making as high-priority data opportunities. Leveraging machine intelligence will improve the speed and accuracy of decisions and also help push decisions to front-line employees making for a more responsive organization. Collaboration via simulations, visualizations, and data sharing platforms allows companies to harness the knowledge of a much broader base of individuals.

37 | © 2010 nGenera Corp. All Rights Reserved. 37 | © 2010 nGenera Corp. All Rights Reserved.

Nauman [email protected]

(416) 863-8825www.nGenera.com

mailto:[email protected]

http://www.ngenera.com/

Survey Results Age Of Unbounded Data June 03 10

Technology

Transcript of Survey Results Age Of Unbounded Data June 03 10