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The Different Applications of Business Analytics

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What are the different applications of business analytics?

  1. Advertising
  2. Supply management
  3. Customer service performance
  4. Employee productivity

 

In the Philippines, leadership training has recently incorporated the subject of business analytics in their programs because it allows people in managerial positions to make more accurate decisions.

Thanks to technological improvements, computers are able to collect information on everything related to business, even from the most unlikely of sources; sensors, phone calls, scanners, etc.

Because of its huge potential, leaders have found different ways to apply business analytics to help their companies grow.

 

Advertising

Video commercials, social media posters, and billboards for companies selling products and services are always pre-planned. Furthermore, there is a lot of calculations that come into these creations and business analytics has allowed marketers to become smarter about how they reach out to customers.

Advertisers and marketers have always had a difficult time basing their plans on objective data. Data can make the entire process of strategizing more efficient by understanding buyer behavior, customer motivation, and what technological devices they are using the most to view these advertisements.

Lastly, data analytics can give your staff more innovative ideas because it is easier for them to gather and analyze the information needed to implement those ideas. For example, Netflix is able to come up with more and more unique campaigns for their films by using data tools to discover the current preferences of their subscribed users.

 

Supply Management

Supply Management

Data analytics has made it easier to supply management teams to cut costs by using algorithms. These algorithms go through sources of data to analyze and question these factors; inventory levels, demand forecasting, order to pay, and supplier quality. According to leadership training in the Philippines, it discovers all of these without the need for manual intervention.

By reading all the important data, companies have been to accomplish these goals:

  • More accurate demand forecasting

‘Demand forecasting’ is used to discover the exact amount of orders months or a year ahead of time. Data analytic tools utilize all sorts of statistical methods to forecast how much your supply chain managers need to order from suppliers.

  • Track transport trucks on transit

Most orders are still fulfilled by truck drivers who deliver it to customers, all within a set deadline. Since buyers are demanding for their purchases to be brought to them in the fastest time possible, managers have been finding ways to make transport logistics a lot more efficient.

By using data analytics to track transport trucks on transit, brands know exactly what needs to change for delivery performance to improve.

  • Using IoT technology to physically assess inventory

IoT (Internet of Things) allows people to collect data from almost any device that is not a computer, such as sensors and even particular appliances.

Because of its capability to read almost anything, supply chain managers have been using IoT on sensing machines that track when new inventory enters and leaves. These sensor machines are also intelligent enough to tell employees if a certain product was damaged. These items collect important information in real time for the company to take immediate action.

 

Customer Service Performance

Customer service is what adds a human dimension to your company, it is the sector that will keep your buyers loyal. Consistently finding ways to improve your department’s customer service performance is an important part of a manager’s leadership development. Additionally, more customer loyalty equals more revenue for the company.

Data is expected to improve customer service by first, letting you get deep insights into the needs of your callers. Second, it allows you to see what mediums of support your customers prefer; phone call, SMS, live chat, or email. Third, it will tell you why some representatives take longer than other co-workers to resolve the issues of their customers, and how to exactly solve the reasons blocking them from improving their performance.

 

Employee Productivity

Employee Productivity

Leadership development requires you and other managers to understand that your people are the lifeblood of the company; they are what keeps business operations going. Thus, it is important to understand the factors which keep your employees productive.

Yet, knowing what motivates your team members to do well is difficult because some leaders find it harder and harder to engage and ask for their feedback. By failing to reach out, employees tend to feel less valued. Not feeling valued can negatively affect their performance.

Data analytics can help you improve employee productivity by giving you tools which tell you the different factors of employee productivity. These tools are usually KPI metrics, work-hour trackers, and accomplishment trackers. If you see there are troublesome information collected from any of these programs, then you know it is time for you to solve them as a manager.

 

Key Takeaway

Data analytics allows business leaders to approach problems in different areas of their companies. Whether it is for advertising or employee productivity, the more information they can collect, the more problems they can solve. All of these different approaches to business analytics allows leaders to see not only what needs to be improved, but how to improve them.

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