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    30 2017

    5 Ways Data Analytics Is Disrupting Business Models

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    5 Ways Data Analytics Is Disrupting Business Models - Cygnet Infotech

    80% of companies predict their industry will be affected in the next three years.

    On Oct 10th, Tencent announced a $1.1 billion investment in Ola, the #1 player in the rapidly growing ride sharing market. But Ola is not alone in challenging the existing business models. Uber, Airbnb, edX, Lyft, Netflix, Society One, TripAdvisor and many more across multiple industries are challenging long-held business models. By coupling new big data technologies and advanced data analytics to uncover new operational and market insights, new untapped customer segments, and new products they are disrupting and changing existing business models.

    Over 90% of companies consider big data and analytics a strategic priority, yet Bain says only 19% of companies have a high quality consistent data!

    Data has become one of the key value sources today! However, companies cannot succeed this transformation if they aim blindly, simply because it’s fashionable or competitors are doing it. They need to know exactly where they’re going, why they’re doing it and the kind of effort they are willing to put into it. For this to happen they need to have clear vision, strategy and use cases to implement. Business need to proactively get into using analytics and have a holistic view of the business. This demands a completely different way of doing business. This call for identifying the key potential areas and setting benchmarks through 5 ways to unearth the tremendous transformative role that data can play in how and where they do business.

    Strategic Analytics

    Strategic analytics implies detail, data-driven, analysis of the entire system to analyze what’s the driving behavior. The key to strategic analytics is doing it in the right order in-order to figure out what to focus on. The flow includes:

    • Step 1 - Competitive Advantage Analytics to identify organization’s competitive advantage, capability strength & weakness
    • Step 2 - Enterprise Analytics to pursue diagnostics at the enterprise level, business unit and business process level
    • Step 3 - Human Capital Analytics for diagnostics at the individual level and HR process with the goal to get actionable insights in defining the right questions.

    It helps in understanding how to deal with occasionally occurring repeated challenges and helps focus on answers to critical questions like:

    • What are the key decisions that drive the most value for us?
    • What new data is available that hasn’t been used in these decisions?
    • What new analytics techniques haven’t been fully explored?

    Platform Analytics

    The second way is to choose platform analytics to understand how infusing analytics into decision making will improving core operations of the business process. It can help the organization harness the power of their data and identify new opportunities. The pertinent questions to ask are:

    • How can we integrate analytics into everyday processes?
    • Which processes can benefit from automatic, repeatable analysis done in real time?
    • Could our back-end system benefit from big data analytics?

    Available through a variety of formats and channels, platform analytics must encompass more than a stack of technologies. Instead, it should be the pulse of the organization, incorporated into all key decisions across sales, marketing, supply-chain, customer experience and other core functions. You do this by developing a strategy across the entire enterprise that includes what you hope to accomplish and how success will be measured.

    Enterprise Information Management

    Almost 80% of vital business information is currently stored in unmanaged repositories, making its efficient and effective use a nearly impossible feat

    With strategic analytics and platform analytics firmly in place, EIM (Enterprise Information Management) helps you optimize social, mobile, analytics and cloud technologies (SMAC) to significantly improve the way information is managed and leveraged across a company.

    By building efficient and agile data management operations with capabilities for information creation, capture, distribution and consumption, EIM can help streamline your business practices, enhance collaboration efforts, and boost employee productivity in and out of your office. When defining an EIM strategy   assess the business requirements, key issues and opportunities for initiating EIM. Identify potential programs and projects that would benefit from an information management initiative and have a higher probability of being successful with one in place.

    Business Model Transformation

    Companies that embrace big data analytics and transform their business models in parallel with it will find new opportunities for revenue streams, customers, products and services. Transformation requires sweeping changes and include:

    • Having a big data strategy and vision that identifies and capitalizes on new opportunities
    • Fostering a culture of innovation and experimentation with data
    • Understanding how to leverage new skills and technologies, and manage the impact they will have on how information is accessed and safeguarded
    • Building trust with consumers who hold vital data
    • Creating partnerships within and outside the core industry
    • Finding ways to gain insight and implement the results quickly

    Every aspect of evolving business models — from forecasting demand to sourcing materials to recruiting and training staff to accounting — is subject to a wave of reinvention.

    Making Data-Centric Business

    Do you generate large volume of data? Could that data benefit other organizations, both inside and outside the industry? The data centric business doesn’t just treat data as an asset but treat data as gold and that’s the source of their core-competitiveness. They are driven by an analytic culture that can be broken down into three categories:

    • Insight: Includes mining, cleansing, clustering, and segmenting the data to understand customers, their networks, influence and product insights.
    • Optimization: Utilize analytics to analyze business functions, processes and models.
    • Innovation: Explore new disruptive business models that foster evolution and growth of your customer base

    Established business models are under attack! Even as data analytics is swiftly overturning the conventions of incumbent industries and reframing the long standing, often implicit beliefs, these Five key applications of data analytics are helping forward-looking companies gain competitive advantage and disrupt business models.

    It is little surprising to see that various sectors like transportation, financial, retail, sales, event management firms, have also kick-started using data analytics to cater to strong technological architecture of data management and data processing. Make your own data analytics model for your business by partnering with Cygnet today. Our data analytics’ expert team will help you translate business ideas to engaging and fruitful business experience. 



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