Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    data analytics in ecommerce
    Analytics Technology Drives Conversions for Your eCommerce Site
    5 Min Read
    CRM Analytics
    CRM Analytics Helps Content Creators Develop an Edge in a Saturated Market
    5 Min Read
    data analytics and commerce media
    Leveraging Commerce Media & Data Analytics in Ecommerce
    8 Min Read
    big data in healthcare
    Leveraging Big Data and Analytics to Enhance Patient-Centered Care
    5 Min Read
    instagram visibility
    Data Analytics Plays a Key Role in Improving Instagram Visibility
    7 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-23 SmartData Collective. All Rights Reserved.
Reading: 5 Ways Companies Use Machine Learning to Improve Workplace Productivity
Share
Notification Show More
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Exclusive > 5 Ways Companies Use Machine Learning to Improve Workplace Productivity
ExclusiveMachine Learning

5 Ways Companies Use Machine Learning to Improve Workplace Productivity

Companies are investing more heavily in machine learning than ever as they strive to maximize productivity.

Ryan Kh
Last updated: August 15, 2022 8:28 pm
Ryan Kh
6 Min Read
5 Ways Companies Use Machine Learning to Improve Workplace Productivity
Shutterstock Licensed Photo - 1890415120
SHARE

Technology has become so advanced that, today, there’s an app for almost anything, from children’s education, to home improvement, to health monitoring, to workplace productivity. Gathering critical data to determine the best action to apply to specific situations has become integral in people’s daily lives.

Contents
1.     Anticipating Changes In Labor Needs2.     Hiring The Right People3.     Using The Power Of Chatbots4.     Making Accurate Sales Forecasts5.     Utilizing Enterprise SearchConclusion

Because of technology, critical decisions are now mostly based on scientific data. This makes every action more precise and error-free, especially in the business world. By using artificial intelligence and machine learning, industries can better cope with their consumers’ demands.

Companies can function better and deliver the best outputs if their employees are happy and productive. The country with the highest percentage of labor productivity is Ireland, with 99.5% productivity despite having only a four-day work week. This only means that longer hours don’t equate to productivity.

Today, companies use machine learning, in particular, to ensure that they achieve the appropriate productivity output for the amount of money they spend on their business operations. Because aside from the need to organize unusual indoor team-building activities to boost employee morale, companies today need to elevate the operational activities they conduct at work to ensure their teams are consistently productive.

More Read

data analytics in healthcare

EKU Notes Data Analytics Is Crucial For Health Awareness For Businesses

Blockchain Will Unblock A Data Problem In Healthcare
Deep Learning Provides Essential Business Elements To eCommerce Brands
Data Driven Insights For A Holistic Digital And Print Marketing Campaign
Business Security Meets Open Source Code: Managing Software Vulnerabilities

Here are some of the ways companies achieve such through machine learning:

1.     Anticipating Changes In Labor Needs

The retail landscape often finds it challenging to keep personnel costs low, while ensuring that customers are happy and satisfied. There are periods when a retail store doesn’t have customers for an extended period and having several staff members handling the store can be utterly unproductive and costly.

A labor scheduling tool that gathers information based on results, which is then entered in the POS, will increase the productivity of a retail store. This tool ensures that crucial metrics, such as personnel hours, items per transaction, and hourly sales, are considered to determine the appropriate number of staff to deploy at specific times of the day.

Hiring decisions will also be guided and labor costs significantly reduced because a labor scheduling tool will help an organization determine if they need to hire full-time or part-time employees. Hiring part-time employees is more cost-effective. And, if the tool predicts that there’s no need for full-time employees, it’d be better and increase a company’s bottom line.

2.     Hiring The Right People

Hundreds of job applications come through the doors of the human resources department daily and filtering these applications so the right people can get hired to perform the essential workplace tasks can sometimes be daunting.  Ordinarily, a person assigned to go through these applications may have biases or could unintentionally allow their emotions to affect their judgment.

When a tool is tasked to filter job applications, it can do so without biases and ignore the appeals to emotion altogether. A tool like a recruiting application that filters the unique qualifications of job applicants can help human resources hire the right people for the company.

The recruitment application will be tasked to watch out for crucial factors inherent in a bad hire and would try their best to avoid this from getting into the pool that’ll move up to the next level of the application process. This way, only applicants that match the values of the company will eventually be onboard to perform relevant tasks for the company.

3.     Using The Power Of Chatbots

Your business can benefit a lot from chatbots. Historical responses on platforms that are automatically saved on the system will be added to the predictive answers of customer inquiries. Now, should any question be unanswerable by a chatbot, it’ll be immediately forwarded to a team member for proper acknowledgement. 

This increases productivity and response time, which is also a valuable component of customer satisfaction.

4.     Making Accurate Sales Forecasts

Information gathered from various channels can efficiently help managers make closer to accurate forecasts. In doing this, proper deployment of manpower can be achieved. Information from all platforms, like social media marketplace, ecommerce stores, and brick and mortar store can be gathered to create sales forecasts that’ll be useful in the production aspect of the business. 

If you know how many sales are coming in, factoring in other crucial details, like events, can give you a more straightforward way of predicting what’s to happen in the near future. This will increase productivity and reduce production waste at the same time.

5.     Utilizing Enterprise Search

Your team members and customers can benefit from enterprise search powered by machine learning.  If you have a massive business, content could be challenging to look for, especially if such pieces are scattered through various channels and platforms. 

With a few clicks on your device, customers and team members can gain access to a mine of information that’ll be useful for their respective tasks. Having access to information will allow people in your organization to accomplish tasks efficiently and more productively.

Conclusion

Labor hours spent doing nothing are wasted money. Ensuring that all people deployed in your organization for the day are functioning at their best and are productive will guarantee higher profits for your company.

TAGGED:machine learning
Share This Article
Facebook Twitter Pinterest LinkedIn
Share
By Ryan Kh
Follow:
Ryan Kh is an experienced blogger, digital content & social marketer. Founder of Catalyst For Business and contributor to search giants like Yahoo Finance, MSN. He is passionate about covering topics like big data, business intelligence, startups & entrepreneurship. Email: ryankh14@icloud.com

Follow us on Facebook

Latest News

trusted data management
The Future of Trusted Data Management: Striking a Balance between AI and Human Collaboration
Artificial Intelligence Big Data Data Management
data analytics in ecommerce
Analytics Technology Drives Conversions for Your eCommerce Site
Analytics Exclusive
data grids in big data apps
Best Practices for Integrating Data Grids into Data-Intensive Apps
Big Data Exclusive
AI helps create discord server bots
AI-Driven Discord Bots Can Track Server Stats
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

machine learning
Artificial IntelligenceMachine Learning

Deep Feature Synthesis Is the Future of Machine Learning

6 Min Read
data catalog big data quality
Big DataData QualityPolicy and Governance

Turbo-Charge Data Scientist Productivity with a Data Catalog

8 Min Read
deep learning and parking system
Machine Learning

How Deep Learning Technology Improves the Efficiency of Parking Management Systems

11 Min Read
options for cybersecurity
Big DataExclusiveITSecurity

Machine Learning Makes VPNs Excellent Options For Cybersecurity

6 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI chatbots
AI Chatbots Can Help Retailers Convert Live Broadcast Viewers into Sales!
Chatbots
ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-24 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?