According to “the entire digital universe is expected to reach 44 zettabytes by 2020.” You read that correctly 40,000,000,000,000,000,000,000 bytes.  Furthermore, they estimate by 2025, 463 exabytes of data will be created each day. That’s 463,000,000,000,000,000,000 bytes of data EACH DAY, and your firm is churning out its share of this data.  So the question isn’t should your company be analyzing its data – the truth is, you can’t afford not to.

There are several ways that businesses are leveraging data analytics to become more efficient and profitable than ever — let’s take a look…

  1. Improve employee productivity and engagement

Organizations are faced with “The Great Resignation” where millions of employees quitting their jobs and leaving their companies for more favorable options.  The firm’s data and HR platforms, enable managers to improve productivity and increase retention.

  1. Streamline operations to be more efficient

Business leaders use data analytics to identify inefficient internal processes and develop new, streamlined workflows that enhance operational efficiency.  For example, a simple analysis of the variability of two operational metrics, will show in an instant which one is more efficient – data analysis makes the decision for you.

  1. Track consumer behaviors to enrich customer experiences

The future of customer service will depend on a robust data analytics strategy. One of the most common uses of data analytics to improve business outcomes is tracking consumer behavior to improve user/customer experiences.  For example, a firm’s call center was getting random and generic online complaints about long hold-times when calling in.  Since the complaints didn’t give details, the firm did an analysis of its data and first determined the day and time period of the majority of calls – as shown in these charts.

Finally, the firm calculated the probability and expected values for the number of calls in order to predict future call volume.  With these results in hand, they simply shifted manpower to where their data told them, and problem solved – no more complaints – the data analysis made the decision for them.

  1. Monitor market trends to launch new products and services

Successful businesses are agile and are constantly monitoring their data.  Consequently, they can launch new products to market quickly based on consumer demand trends.  For example, retailers can measure their customers’ purchase frequency among high-priority customer segments to better understand the products that customers want. The same retailers can also measure when customers shift to new products to identify which SKUs are distinctive and which ones are redundant. Not only retailers use data to improve products and services. Digital-first companies like Uber, Netflix, and Google also use customer data to track how people use their products to make changes.  Sometimes the best decision is to discontinue a product or service, but don’t worry, your data will tell you that.

  1. Measure performance of marketing campaigns

Marketing campaigns must be data-driven, from conception to execution. To launch a data-driven marketing campaign, teams set key performance indicators (KPIs) to determine metrics for success. Next, marketing teams must gather descriptive data about their target market, distribution channels, trends, etc. Marketing teams can A/B test advertisements to determine which written and visual messages resonate with their demographic (cross-sectional data in statistical terms). Finally, marketing teams monitor and review the campaign results to identify areas of strength and weakness.

A few statistical methods we use in Marketing include:

Cross-sectional and time period variance to study the effectiveness of campaigns.

Logistic regression – the analytic pillar of database marketing.

Regression analysis to study price elasticity – critical in marketing.

  1. Use data insights to inform business strategies 

A business strategy is only as good as its data. Data-driven business strategies effectively use past situations to predict future possibilities and help leaders prescribe the best path forward. In a famous example, Netflix used Big Data and business intelligence to become one of the best-known brands of all time. Netflix uses predictive analysis to recommend new entertainment to its users and even to create new movies and television shows. After analyzing 30 million streaming habits a day, over 4 million subscriber ratings, and 3 million searches, Netflix developed new content, including hit TV shows like “House of Cards” and “Arrested Development.” This is a shining example of how successful a company can be when built on a data-driven business model.

  1. Lead teams with data-driven decision making

According to Forbes, there are two distinct ways to use data as a leader — data-driven or data-informed. Data-driven leaders listen to the data and allow the facts to either prove or disprove their hypotheses. These leaders are not afraid to be proven wrong by data. However, data-informed leaders use data selectively to justify their actions regardless of the findings. Leaders should strive to be data-driven and make decisions that benefit the greater teams and organization.

Applied Business Statistics and Data Analytics

These are of critical importance in business nowadays – far more than in previous years because of the technology boom.  Your firm, and your competition’s, now has vast amounts of data in a diverse number of categories, and your job is to mine and analyze it.  Success now relies so much more on in-depth data analysis rather than on gut feeling alone.

Get the right tools to be an effective leader, and to grow your business and your career.  The techniques are here, and the long-term benefits of adopting them can be huge.