Key Insights

Advanced Analytics: The Key to Becoming a Data-Driven Enterprise (Key Insights)

A new study on analytics adoption by Forbes Insights and Cisco shows a significant gap between mature organizations and those who risk falling behind. But by studying the patterns among 207 large enterprises in North America and Europe valuable lessons emerge. With mature, enterprise-wide analytics strategies in place, the leaders in analytics represented only 16 percent of the total sample. However, they are seeing compelling results, ranging from increases in sales and profits to an improved ability to outmaneuver competitors. And their best practices offer a valuable model for others.

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Insight 01

What Drives Executives To Invest in Analytics and Smart Data?

60% of analytics leaders report revenue growth greater than 7%

Executives seek a range of benefits from their analytics initiatives. Many are also using data analysis to drive strategic decisions; for example, around creating new revenue streams. But data alone isn’t enough — real insight comes from understanding the important questions that need to be answered. That’s what improves decision making.


Top Reasons to Invest in Analytics

  1. Improve product quality
  2. Improve employee satisfaction
  3. Increase customer satisfaction
  4. Create new revenue
  5. Insights into customer behaviors
  6. Expand customer base
  7. Improve profitability

Insight 02

The Key to Developing an Enterprise-Wide Analytics Strategy: Keep the Balance

Success in analytics requires the right investments. But it also demands a commitment from senior leaders. They must ensure that analytics is pervasive across the enterprise while also highlighting specific departmental areas of excellence — in effect, a “hub and spoke” model that balances both areas.

30% of companies have implemented centralized analytics that are used by all departments


Balancing Centralized and Department Analytics:

  1. Collecting data and linking to data analysis
  2. Interconnecting different data sets from organizational functions
  3. Linking analytics to the decision-making process
  4. An integrated approach of data sourcing, model building, and organizational transformation

Insight 03

IT Modernization: the Backbone of Successful Analytics Initiatives

The most fundamental component of a successful analytics strategy is data — extensive, accurate information sets. Intelligent networks use sensors and other tools for real-time data collection and can learn and adapt to changing conditions.

74% of survey respondents indicated intelligent networks improve their organization’s ability to collect and aggregate important data


Activities organizations have aligned to analytics initiatives:

  1. Modernizing the IT infrastructure
  2. Capturing quick wins
  3. Developing analytics governance policies
  4. Drawing top talent for analytics expertise
  5. Creating new leadership roles such as chief data officer (CDO) responsible for data and analytics

Insight 04

The Next Step for Analytics: AI, Machine Learning, and Predictive Modeling

More than half of executives in our survey believe analytics will be critical to maintaining and growing market share. And that’s a trend that will only accelerate as emerging technologies like artificial intelligence, machine learning, and predictive modeling add a new dimension to analytics.

While building the right foundation is critical, traditional platforms alone are not enough for an organization to gain an advantage over competitors.

36% of analytics leaders have dedicated more than 15% of their budgets to analytics initiatives.

They’ve implemented and previously invested in more advanced tools.

  • 73% Invested in predictive analytics
  • 64% Invested in machine learning
  • 45% Invested in artificial intelligence

Insight 05

Without Alignment Between IT and the Business, Initiatives Will Falter

Teamwork among stakeholders throughout the enterprise is essential, including close collaboration between the IT staff and business managers. Analytics leaders are far more likely than others to describe collaboration between IT and business units as “excellent.”

Only 15% of executives surveyed rate their analytics collaboration between IT and business as “excellent.”

Analytics investments suffer due to the lack of collaboration.

57% believe that poor collaboration results in analytics investments that fail to provide business people with the information they need.


Insight 06

Top-Down Leadership Plus Bottom-Up Analytics Equals a Winning Culture

Driving analytics through governance policies

  1. Identify analytics-savvy influencers within the organization – people who may not have the most senior positions but can sway peers to adopt change
  2. Uncover talent gaps needed to be filled by new hires or outside partners
  3. Identify business initiatives where data-driven decision making can deliver quick, clearly documented benefits
  4. Use results to promote the wider adoption of analytics techniques, justifying investments in advanced tools, such as AI
  5. Develop a cross-functional analytics team, including stakeholders in technology, business, operations, legal and HR
  6. The team develops governance policies for promoting C-level mandates for analytics use throughout the enterprise

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