Companies and organizations can use data and analytics to not only improve performance, but change how business gets done by transforming themselves into what we call insight-powered enterprises. An insight-powered enterprise is able to drive its strategy with data-driven insights and inform its actions through analytics.
Learn more about becoming an insight-powered enterprise below.
We have identified five key development points to help companies transition into becoming insights-powered enterprises:
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1. Measuring what matters to align action with strategy and enforce accountability
Insight-powered enterprises use insights in developing their business strategies to change the game.
To measure what matters, companies should focus on the following:
Leverage predictive analytics to identify key drivers of growth.
Employ a closed loop process to measure impact and results.
Align individual incentives to establish accountability for improvements.
2. Optimizing decision processes to embed analytics and insights into processes at the point of decision
The development of analytics is of no business value if the information is not integrated into the business process where it can inform an action.
In order to optimize decision processes with the power of analytics, companies should:
Redesign business processes to infuse data-driven insights in support of decisions.
Sustain agile decision processes by learning to fail fast.
Leverage the app concept to enable end-to-end workflow for specific business problems.
Minimize information overload by providing the user with only the information that supports the next best action.
Our research shows that more than twice as many High Performing companies are adapting and embedding analytics in their decision-making processes as Low Performing companies
(79 percent to 34 percent).
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4. Deploying an agile operating model to redefine how analytics is governed and deployed across the enterprise
Insight-powered enterprises employ agile operating models to act quickly upon key insights.
We believe that analytics delivery must be a blend of rapid insight, test and learn, and scaled proven solutions. To accomplish this, companies need to move away from lengthy processes and complex, layered hierarchies, and haphazard talent sourcing.
To deploy an agile operating model, companies should take the following steps:
Establish an insights lab to focus on key strategic business questions.
Leverage an industrialization team to scale proven solutions.
Efficiently deliver proven, recurring services while monitoring and maintaining service quality.
Implement a governance model oriented on speed to capability, pace of adoption and value realization.
Position IT as a key enabler and change agent in the analytics transformation.
Follow a structured approach to analytics transformation.
Many companies are elevating analytics by establishing a Chief Data and Analytics Officer role. The CDAO is responsible for establishing the goals and strategies to support the analytical needs of the company.
Download Launching an Insights-Driven Transformation
Read Launching an Insights-Driven Transformation, and discover the three common characteristics of organizations with low analytics maturity.
5. Developing an analytics culture to fundamentally change how analytics is used to drive decisions from facts and insights
Metrics, analytics, insights, agile processes, data and technology will only help a business if the business adopts them.
To develop an analytics culture, companies should:
Establish strong executive sponsorships to communicate and endorse analytics goals.
Take a design-led approach to the user experience through intuitive analytics technologies.
Continually adjust the operating model, processes and technologies.
Drive adoption through individual performance goals.
Adapt the organization’s decision-making processes through targeted branding and communication efforts.
Recent research reveals that High Performing organizations are much better at embedding analytics in fact-based decision making to develop a competitive advantage.
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The company teamed with Accenture on a multiyear transformational program to:
Define a vision, strategy and priority capabilities for analytics
Develop a dedicated operating model and organization
Prove the value of analytics through proof of concepts (POCs)
Scale the delivery of analytics capabilities by providing the supporting technology and skills.
With Accenture’s help, the company can now leverage analytics to focus on value-generating opportunities and capture the potential benefits estimated at more than $150 million across functions.
Read the case study, or download the PDF
Going forward, companies should:
Align on a common set of metrics and continuously measure what matters.
Change business processes so that analytics are integral to the output.
Organize to deliver analytics as a core competency.
Establish an operating model that facilitates analytics.
Embrace new technologies to help keep pace within their industry.
Develop a culture of analytics where business is driven from insights, not tradition or hunches.
The journey to analytics maturity is long and complex, but provides significant rewards along the way. With the power of today’s technology and a receptive culture, results can be seen in weeks, rather than in months or years.
Analytics has moved from being an integral part of an organization to being ubiquitous, with each win making change easier and building momentum toward creating the insight-powered enterprise.
DOWNLOAD THE REPORT [PDF]
About Accenture Applied Intelligence
Accenture Applied Intelligence, helps clients to use analytics and artificial intelligence to drive actionable insights, at scale. Accenture Applied Intelligence applies sophisticated algorithms, data engineering and visualization to extract business insights and help clients turn those insights into actions that drive tangible outcomes—to improve their performance and disrupt their markets.
With deep industry and technical experience, Accenture Applied Intelligence provides services and solutions that include, but are not limited to: analytics-as-a-service through the Accenture Insights Platform, continuous intelligent security, machine learning, and IoT Analytics.
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