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5 Ways Data Analytics Is Disrupting Business Models

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5 Ways Data Analytics Is Disrupting Business Models

Data is now as good as gold. Having an effective data collection and analysis strategy is not longer optional if you wish to succeed.

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On October 10, 2017, Tencent announced a $1.1 billion investment in Ola, the number one player in the rideshare market. But Ola is not alone in challenging established business models.

Look at the rise of Uber, Amazon, Airbnb, edX, Netflix, Society One, and TripAdvisor. They all looked at a stalwart in their industry and said: “I can do better.”

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

With cloud computing, even the smallest start-up can couple big data technology with advanced data analytics. Every day, the power to uncover new operational and market insights, and untapped customer segments, grows.

Over 90% of companies consider big data and analytics a strategic priority, yet Bain says only 19% of companies are mining high-quality data consistently!

Most of your competitors probably aren’t taking advantage of data technology, but are you? If you’re slacking, you can guarantee there’s a start-up or innovative competitor who has their sights on you.

The Power of Data

Big data has become a powerful resource. Companies cannot succeed if they aim blindly at potential customers. To thrive, you need to know exactly where you’re going, why you’re going there, and what kind of effort you’re willing to put into the journey.

Big data is your guide.

However, you need to have a clear vision, a strategic approach and use cases to go forward with your big data discoveries. You need to get involved in using analytics so you can have a holistic view or your business.

To accomplish this, redefine how you process data and set benchmarks for how that data will be used.

5 Ways to Unearth Transformative Data

1. Strategic Analytics

Strategic analytics is detailed, data-driven analysis of your entire system to help you determine what’s driving customer and market behavior.

The key to strategic analytics is doing it in the right order:

  • Step 1 – Competitive Advantage Analytics to identify your capabilities, strengths, and weaknesses.
  • Step 2 – Enterprise Analytics to get diagnostics at the enterprise, business unit, and business process levels.
  • Step 3 – Human Capital Analytics for diagnostics at the individual level to get actionable insights.

The data should answer critical questions like:

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

2. Platform Analytics

This helps you fuse analytics into your decision-making to improve core operations. It can help your company harness the power of data to identify new opportunities.

The important questions to ask include:

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

Platform analytics must include more than a stack of technologies. As it’s available via many formats and channels, it can be used to check the pulse of your organization.

It will help you incorporate data analysis into key decisions across all departments, including sales, marketing, the supply chain, customer service, customer experience, and other core business functions.

Enterprise Information Management (EIM)

Almost 80% of vital business information is stored in unmanaged repositories. With strategic and platform analytics already in place, EIM helps you take advantage of social, mobile, analytics, and cloud technologies (SMAC) to improve the way data is managed and used across the company.

By building agile data management operations with tools for information creation, capture, distribution and consumption, EIM will help you:

  • Streamline your business practices.
  • Enhance collaboration efforts.
  • Boost employee productivity in and out of the office.

When defining your EIM strategy, identify the business requirements, key issues, and opportunities for initiating EIM. Also, identify potential programs and projects whose success rates would benefit from EIM.

4. Business Model Transformation

Companies that embrace big data analytics and transform their business models in parallel will create new opportunities for revenue streams, customers, products, and services.

From forecasting demand and sourcing materials to accounting and the recruitment and training of staff, every aspect of your business can be reinvented.

Needed changes 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 managing the impact they have on how information is accessed and safeguarded.
  • Building trust with consumers who hold vital data.
  • Creating partnerships both within and outside your core industry.
  • Finding ways to gain insight and implement results quickly.

5. Making a Data-Centric Business

Do you generate a large volume of data? Could that data benefit other organizations, both inside and outside your industry?

Data-centric business isn’t just an asset, it’s currency. It’s the source of your core competitiveness, and it’s worth its weight in gold.

There are three main categories of data analytics:

  • Insight: Includes mining, cleansing, clustering, and segmenting data to understand customers and their networks, influence, and product insights
  • Optimization: Analyzing business functions, processes, and models.
  • Innovation: Exploring new, disruptive business models to further the evolution and growth of your customer base.

Established Business Models Are Under Attack

Data analytics is swiftly overturning the way we do business. These five transformative applications of data analytics will help you become a forward-thinking company and gain a competitive advantage in the marketplace.

There is no industry that data analytics can’t benefit.

Learn how taking a DataOps approach will help you speed up processes and increase data quality by providing streamlined analytics pipelines via automation and testing. Learn More.

data analytics ,data science ,big data

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