Understanding the Role of Power BI in the Manufacturing Industry

Integration of technology in different industries and business sectors has been obvious. The digital transformation streamlines various processes effortlessly. Although the manufacturing industry has been slow to embrace technology. But the right time is here for the production sector to improve decision making and performance from data analytics.  

Industry 4.0 when combined with the power of the latest technological development of AI, advanced visualization and analytics, robotics and IoT powered devices can provide manufacturers with the potential to collect, store, visualize and utilize data in daily factory operations.  

Through advanced business intelligence and analytics, plant managers can get recommendations about possible improvements.  

The manufacturing industry is constantly looking for improved solutions to speed up production and automate large scale industrial processes. In this post, we wish to throw some light on power bi data analytics implementations and how they can bring a transformation for the manufacturing industry.  

Why should everyone in manufacturing utilize the industry 4.0 revolution with Power BI? 

Industry 4.0 involves a set of technologies for several processes. Even though the concept of industry 4.0 is a little hard, the manufacturing plants which use this solution have much faster production than companies still relying on conventional methods. Advanced data analytics and processes automation combined with connectivity can enhance production efficiency exponentially. Data analytics through power bi have helped plant managers to customize products, decrease time to time, increase efficiency and create a more sustainable and profitable business model optimized for service productivity.  

For companies committed to streamline their supply chain, align operations, and crush production challenges, data analytics with power bi can help you achieve it all.  

Before moving on to the benefits of power bi and analytics, let’s see some major data challenges of the manufacturing industry.  

1. In manufacturing, there are so many processes and while the data is collected from several sources, it is presented inconsistently, making it difficult to read and draw insightful conclusions. Some companies gather data successfully but fail to comprehend and further utilize it.  
2. Another challenge is the integration of data analytics with traditional manufacturing systems such as ERPs, production planning systems and others.  
3. Even when the manufacturing department generates huge data, it fails to manage and coordinate the pace of storage management systems.  
4. As the number of processes increases and the production grows, the complexity of data sore high which then need better visualization and analytics tools. Although it’s not the responsibility of the manufacturer to solve this issue, they must be aware of what a data analytics tool like power bi can do for complex data analysis.   
5. An industrial data collection system with limited computing power might put the entire company at risk as there are underlying threats of cyber attacks, online leaks, unauthorised access, and other security issues.  

We have discussed some of the primary data challenges, now let’s see how power bi can help mitigate these threats.  

How data analytics solutions of Power BI can transform the manufacturing industry? 

Detailed reports, graphs and charts in power bi can be explicitly used by companies to draw actionable insights for core manufacturing issues such as: 

• Which products bring the most customers and which yields lower profitability? 
• What are the weak links in the manufacturing process? For instance which raw material vendor can halt manufacturing the most?
• How to perform shipment performance, transportation cost, and several other KPIs of the business? 

The applications of power bi data analytics reports are many in the manufacturing industry. The primary aim for most managers is to improve productivity growth. Other important areas of inefficiency are supply chain management, prediction of sales and marketing expenses, calculation of equipment performance, and more.  

Advanced data analytics can provide a high ROI with intuitive insights in these particular areas of a manufacturing plant. Also, the use of data analytics and visualization will help to create better revenue streams built around the product quality of a manufacturing company.  

Benefits of power bi data analytics features: 

• Low operation costs  

Imagine if employees had access to a custom dashboard to process an instant supply chain analysis or an enterprise-level custom dashboard of sales to monitor all the revenue sources on one screen. This is simply possible through power bi dashboard visualization features in seconds. Manufacturing managers and employees can read complex data in easy to read graphical formats. They access the ability to handle ad hoc queries and share insights about workflows too.  

Such insightful analysis can reduce raw material waste, speed up funding for the most in-demand products, and improve the potential of a manufacturing unit.  

• Maintaining human resource and automation  

For various manufactures, it is not simple to handle automated processes and warehouses as they have to decide about where to keep human labor for certain roles. Sometimes human supervision is necessary to maintain the quality of the product and its seamless production. Workforce analytics solutions in power bi can help manufactures evaluate ROI and employ staff along with automation where required.  

• Incredible management of supply chain  

With the assistance of power bi, manufacturers can analyze supply chain logistics data regularly for timely product deliveries and ultimate services. Such detailed analysis of each batch shipment allows managers to monitor consignment costs, performances and settle contracts.  

A supply chain management dashboard in power bi can help one measure repair costs, transportation expenses, equipment issues, and other KPIs efficiently. The data is presented in visually attractive formats to gain insights based on previous and real-time data to make informed business decisions.  

• Enhanced decision making  

Data analytics and power bi make decision making very intuitive for managers and come up with unique solutions to rectify operational issues. Power bi processes millions of rows of data instantly and present in a visual format to help decision-makers catch inefficiencies and make efficient decisions for better organizational performance.  

Data is the future  

The organizations adopting data-driven manufacturing are actively dispersing both external and internal problems. Power bi data analytics is a strategic move to get speedy results and performance for your production business as well.  

If you are ready to take a step towards a better future and create a lasting impact through data, talk to our power bi development company and start your data analytics voyage. 

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How to Build an Impressive Data Science Resume?

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The Future of Business Analytics is Here

• Business analytics has moved from the sidelines to the forefront
• AI-based technology has revolutionized the field
• Real-world examples of BA success.

Gone are the days when a BA’s  role was as a requirements note taker [1], or  when data interpretation was the responsibility of a small team of programmers.  In the last ten years, Business analytics has grown from a simple description of predictive and statistical tools to an umbrella term covering a complex spectrum of business intelligence and analytics. BA combines applications, skills, technologies, and processes to provide data-based insights for businesses. Big data is leveraged along with statistics to develop markets, evaluate customer behavior and optimize revenue streams. 

A new generation of  AI-based BI tools have resulted in sweeping changes to the entire data analytics process, enabling the creation of actionable insights from complex data. Companies that implement AI are certain to edge ahead of their competitors, improving performance and generating higher revenue.[2]

Where Business Analytics is Booming

Industries that are at the forefront of the business analytics revolution include:

• Banking and Finance: Analytics aids in the detection of fraud, evaluation of credit risk and prediction of delinquency. For example, Mastercard business analysts built a cross-border ATM Fraud Rules Engine that resulted in a 65% Decrease in ATM Fraud [3].
• Customer service: BA can help to reduce churn rate (customer loss) by using big data to route calls, maintain adequate staffing levels, and catch issues early on in the customer service process. One notable success was seen by broadband communications, services and solutions provider XO Communications, who reduced churn rates by almost 50 percent with the assistance of IBM predictive analytics software [4].
• Education: Data can be analyzed to predict student outcomes, analyze deficiencies in student learning and create a plan for improvement. Intervention can happen earlier, before a student has fallen too far behind [5]. For example, The University of Wolverhampton partnered with student software and services provider Tribal to develop learning analytics software. The tool predicts student success with 70 percent accuracy [6].
• Farming: BA can help farmers boost yields, manage pests and crop diseases and limit pesticide use while maximizing per-acre production. For example, WinField United, the Land O’ Lakes seed and crop-protection division analyzes millions of data points from diverse sources to assist farmers with their goals [7].
• Healthcare: Analytics can benefit patients by assessing risks and suggesting preventative care measures. It can also be used to maintain adequate staffing levels and track trends in a wide variety of areas including new technology, procedures to improve outcomes, or tracking of disease outbreaks. Electronic Health Records, which capture condition-specific information like clinical orders, clinical findings and laboratory results, have become a primary sources of information on the health and well-being of patients [8]. 
• Marketing: BA can help to predict sales, maintain a budget, and analyze consumer behavior. Trends in consumer loyalty can be tracked, with different brand messages analyzed for effectiveness. As an example, behavioral targeting collects data on consumer browsing activities by placing digital tags in browsers. These tags track and aggregate consumer behavior, resulting in the serving of more relevant advertising [9].
• Sports: Sports BA is booming, enabling sports business professionals strategize, promote a company’s financial performance, and maintain or improve a competitive advantage [10]. Business analytics has been used in Major League Baseball to show that starting pitchers lose effectiveness when they cycle through the batting lineup. This has resulted in a big increase in relief pitchers [11].

These are just a few examples to highlight the growing trends. As the science of business analytics continues to grow, it is on track to become  “the world’s hottest market for advanced skills” [12].  As more and more businesses incorporate advanced data techniques and gain a competitive edge, the market for business analysis will continue to soar.

References

Image: Author

[1] The Future of Business Analysis

[2] From Business Intelligence to Artificial Intelligence

[3] Business Analytics for Data Science

[4] XO Communications reduces customer churn rate by 50% using IBM Busi….

[5] The Future of Business Analytics

[6] Learning from Data to Improve Student Outcomes

[7] Using Analytic to Improve Customer Engagement

[8] Applications of Business Analytics in Healthcare

[9] Behavioral Targeting: A Case Study of Consumer Tracking on Levis.com

[10]  Application of Business Analysis in Sports Business

[11] Madden: Hey, Rob Manfred! The analytic geeks are ruining starting p…

[12] Mobilizing Your C Suite For Big Data Analytics

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Algorithms for decision making: excellent free download book from MIT

https://algorithmsbook.com/

MIT press provides another excellent book in creative commons.

Algorithms for decision making: free download book

I plan to buy it and I recommend you do. This book provides a broad introduction to algorithms for decision making under uncertainty.

The book takes an agent based approach

An agent is an entity that acts based on observations of its environment. Agents

may be physical entities, like humans or robots, or they may be nonphysical entities,

such as decision support systems that are implemented entirely in software.

The interaction between the agent and the environment follows an observe-act cycle or loop.

• The agent at time t receives an observation of the environment
• Observations are often incomplete or noisy;
• Based in the inputs, the agent then chooses an action at through some decision process.
• This action, such as sounding an alert, may have a nondeterministic effect on the environment.
• The book focusses on agents that interact intelligently to achieve their objectives over time.
• Given the past sequence of observations and knowledge about the environment, the agent must choose an action at that best achieves its objectives in the presence of various sources of uncertainty including:

1. outcome uncertainty, where the effects of our actions are uncertain,
2. model uncertainty, where our model of the problem is uncertain,
   3. state uncertainty, where the true state of the environment is uncertain, and
3. interaction uncertainty, where the behavior of the other agents interacting in the environment is uncertain.

The book is organized around these four sources of uncertainty.

Making decisions in the presence of uncertainty is central to the field of artificial intelligence

Table of contents is

Introduction

Decision Making

Applications

Methods

History

Societal Impact

Overview

PROBABILISTIC REASONING

 Representation

Degrees of Belief and Probability

Probability Distributions

Joint Distributions

Conditional Distributions

Bayesian Networks

Conditional Independence

Summary

Exercises

viii contents

 

Inference

Inference in Bayesian Networks

Inference in Naive Bayes Models

Sum-Product Variable Elimination

Belief Propagation

Computational Complexity

Direct Sampling

Likelihood Weighted Sampling

Gibbs Sampling

Inference in Gaussian Models

Summary

Exercises

 Parameter Learning

Maximum Likelihood Parameter Learning

Bayesian Parameter Learning

Nonparametric Learning

Learning with Missing Data

Summary

Exercises

 Structure Learning

Bayesian Network Scoring

Directed Graph Search

Markov Equivalence Classes

Partially Directed Graph Search

Summary

Exercises

 

Simple Decisions

Constraints on Rational Preferences

Utility Functions

Utility Elicitation

Maximum Expected Utility Principle

Decision Networks

Value of Information

Irrationality

Summary

Exercises

SEQUENTIAL PROBLEMS

 Exact Solution Methods

Markov Decision Processes

Policy Evaluation

Value Function Policies

Policy Iteration

Value Iteration

Asynchronous Value Iteration

Linear Program Formulation

Linear Systems with Quadratic Reward

Summary

Exercises

Approximate Value Functions

Parametric Representations

Nearest Neighbor

Kernel Smoothing

Linear Interpolation

Simplex Interpolation

Linear Regression

Neural Network Regression

Summary

Exercises

 Online Planning

Receding Horizon Planning

Lookahead with Rollouts

Forward Search

Branch and Bound

Sparse Sampling

Monte Carlo Tree Search

Heuristic Search

Labeled Heuristic Search

Open-Loop Planning

Summary

Exercises

 

 Policy Search

Approximate Policy Evaluation

Local Search

Genetic Algorithms

Cross Entropy Method

Evolution Strategies

Isotropic Evolutionary Strategies

Summary

Exercises

 Policy Gradient Estimation

Finite Difference

Regression Gradient

Likelihood Ratio

Reward-to-Go

Baseline Subtraction

Summary

Exercises

Policy Gradient Optimization

Gradient Ascent Update

Restricted Gradient Update

Natural Gradient Update

Trust Region Update

Clamped Surrogate Objective

Summary

Exercises

 Actor-Critic Methods

Actor-Critic

Generalized Advantage Estimation

Deterministic Policy Gradient

Actor-Critic with Monte Carlo Tree Search

Summary

 

 Policy Validation

Performance Metric Evaluation

Rare Event Simulation

Robustness Analysis

Trade Analysis

Adversarial Analysis

Summary

Exercises

MODEL UNCERTAINTY

 Exploration and Exploitation

Bandit Problems

Bayesian Model Estimation

Undirected Exploration Strategies

Directed Exploration Strategies

Optimal Exploration Strategies

Exploration with Multiple States

Summary

Exercises

 Model-Based Methods

Maximum Likelihood Models

Update Schemes

Exploration

Bayesian Methods

Bayes-adaptive MDPs

Posterior Sampling

Summary

Exercises

Model-Free Methods

Incremental Estimation of the Mean

Q-Learning

Sarsa

Eligibility Traces

Reward Shaping

Action Value Function Approximation

Experience Replay

Summary

Exercises

 

 Imitation Learning

Behavioral Cloning

Dataset Aggregation

Stochastic Mixing Iterative Learning

Maximum Margin Inverse Reinforcement Learning

Maximum Entropy Inverse Reinforcement Learning

Generative Adversarial Imitation Learning

Summary

Exercises

PART IV STATE UNCERTAINTY

19 Beliefs 373

Belief Initialization

Discrete State Filter

Linear Gaussian Filter

Extended Kalman Filter

Unscented Kalman Filter

Particle Filter

Particle Injection

Summary

Exercises

20 Exact Belief State Planning 399

Belief-State Markov Decision Processes

Conditional Plans

Alpha Vectors

Pruning

Value Iteration

Linear Policies

Summary

Exercises

Offline Belief State Planning 

Fully Observable Value Approximation

Fast Informed Bound

Fast Lower Bounds

Point-Based Value Iteration

Randomized Point-Based Value Iteration

Sawtooth Upper Bound

Point Selection

Sawtooth Heuristic Search

Triangulated Value Functions

Summary

Exercises

Online Belief State Planning 

Lookahead with Rollouts

Forward Search

Branch and Bound

Sparse Sampling

Monte Carlo Tree Search

Determinized Sparse Tree Search

Gap Heuristic Search

Summary

Exercises

Controller Abstractions 

Controllers

Policy Iteration

Nonlinear Programming

Gradient Ascent

Summary

Exercises

PART V MULTIAGENT SYSTEMS

Multiagent Reasoning 

Simple Games 

Response Models

Dominant Strategy Equilibrium

Nash Equilibrium

Correlated Equilibrium

Iterated Best Response

Hierarchical Softmax

Fictitious Play

Gradient Ascent

Summary

Exercises

Sequential Problems 

Markov Games

Response Models

Nash Equilibrium

Fictitious Play

Gradient Ascent

Nash Q-Learning

Summary

Exercises

State Uncertainty 

Partially Observable Markov Games

Policy Evaluation

Nash Equilibrium

Dynamic Programming

Summary

Exercises

Collaborative Agents 

Decentralized Partially Observable Markov Decision Processes

Subclasses

Dynamic Programming

Iterated Best Response

Heuristic Search

Nonlinear Programming

Summary

Exercises

APPENDICES

Mathematical Concepts

Measure Spaces

Probability Spaces

Metric Spaces

Normed Vector Spaces

Positive Definiteness

Convexity

Information Content

Entropy

Cross Entropy

Relative Entropy

Gradient Ascent

Taylor Expansion

Monte Carlo Estimation

Importance Sampling

Contraction Mappings

Graphs

 Probability Distributions

 Computational Complexity

Asymptotic Notation

Time Complexity Classes

Space Complexity Classes

Decideability

 

 Neural Representations

Neural Networks

Feedforward Networks

Parameter Regularization

Convolutional Neural Networks

Recurrent Networks

Autoencoder Networks

Adversarial Networks

 Search Algorithms

Search Problems

Search Graphs

Forward Search

Branch and Bound

Dynamic Programming

Heuristic Search

 Problems

Hex World

2048

Cart-Pole

Mountain Car

Simple Regulator

Aircraft Collision Avoidance

Crying Baby

Machine Replacement

Catch

F.10 Prisoner’s Dilemma

Rock-Paper-Scissors

Traveler’s Dilemma

Predator-Prey Hex World

Multi-Caregiver Crying Baby

Collaborative Predator-Prey Hex World

 

 Julia

Types

Functions

Control Flow

Packages

Convenience Functions

Book link

Algorithms for decision making: free download book

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Introducing Pillars of Data Observability

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Mobile App Development Trends in 2021

            

     

Mobile app technology continues to grow. To expand their offerings and consumer reach, businesses around the world are moving to mobile apps. Thanks to their great success and usefulness, they often represent a massive opportunity for companies and enterprises.

Let’s take a look at the best mobile app development trends:

| Machine Learning

The convergence of mobile app development and machine learning, and artificial intelligence has made our mobile environment increasingly popular.

Currently, AI and ML have dominated mobile app growth patterns and made our lives easier. Just give the machines your orders, and you can get many things done quickly.

Businesses can streamline and streamline various complex business processes.

They can quickly identify customer interests, provide user-specific feedback and simplify business online.

| Internet of Things

The most innovative technology that has taken the tech world by storm is the Internet of Things (IoT). This technology has provided users with a convenient environment to connect to various IoT devices in real-time.

| Cross-Platform Mobile Application Development

It is the best way to build applications that work well across all platforms. We are experts in cross-platform application development and have made most of our applications this way. Cross-platform app development costs about 40% less to develop and 25% less to maintain in the long run than native app development.

| Wearable devices

The wearable technology trend has been on the rise for years. Many organizations have incorporated this technology into their ecosystem to provide their consumers with an always seamless experience—this technology uses smartwatches, fitness bands, and tracking devices.

These IoT devices allow the application to monitor all the activities a person performs during the day.

Users can monitor their heart rate, oxygen levels, blood pressure, and the number of kilometers walked per day, among other things.

According to Statista, there will be 1.1 billion wearable devices by 2022. In addition, there will be a gold rush in the creation of mobile applications for the Internet of Things in the coming years.

| Gamification of applications

Want to attract more customers and improve app purchases? Then gamification is the answer. Yu-Kai Chou uses the term “human-centric approach” to describe how to incorporate the enjoyable experiences of games into digital products. Gaming encourages people to do different things, from downloading images to performing repetitive tasks, by making things desirable to individuals.

In mobile applications, gamification is helpful because the elements of games create a playful environment for users. There are several reasons why this strategy should consider, but the main one is that gamification is a good choice when the goal is to balance user acquisition and retention. Essentially, you can use gamification to build a mobile app that delivers sustainable growth for your customers.

| Cloud-based applications

Smartphone users have recently created demands and desires for cloud-based mobile applications. As a result, all mobile app designs have become complex package designs that require a lot of attention. Mobile apps needed more space on the mobile phone at that time, and working with a mobile app became partially sluggish without the cloud.

| AI 

When we talked about trends in mobile app development, artificial intelligence (AI) was the topic that came up most often last year. From enriching the customer experience to replacing human assistants (e.g., Google Assistant on mobile phones), AI leads the way in almost every market.

Could machine learning be far behind and AI ahead? Together, all these tools improve solutions, spot trends, and make business processes 100 times faster and simpler for stakeholders.

| Low code

Low-code is a visual approach to app development. To enable rapid delivery of different software solutions, low-code abstracts and automates every application life cycle. It breaks down the traditional silos of business and IT to foster continuous collaboration.

The adoption of low-code development platforms has been driven by increased market demand for technology solutions and a shortage of professional developers.

| No code

A no-code framework is a development platform that uses a visual development environment that allows laypeople to build applications by adding application components to create a complete application using methods such as drag and drop. With the no-code framework, users do not need previous coding experience to build applications.

Too good to be true, it seems. Non-technical business users are designing full-fledged applications themselves! Great marketing, but it doesn’t work, does it? To build an app that even comes close to working, you need talented coders.

But low-code is not the only natural way. It happens. It’s changing the industry, and it’s leading to publicity.

| Enterprise management

As technology and its functions evolve, businesses are changing at the same time. They seek to modernize their current way of working and embrace the enterprise’s versatility to improve processes, workflows, employee morale, productivity, performance, and other parameters.

As a result, companies are increasingly turning to enterprise applications for growth. Companies are focusing on creating robust and scalable enterprise software for enterprises and their subsidiaries worldwide through React Native app development or Ionic app development.

| Conclusion

These are the best mobile app development trends that enterprises will be happy to follow in 2021. They will surely help them enjoy positive growth. Contact top app development companies in India and get the best results for your work within the timeframe. 

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IPTV and Video Statistics

100 million people view some form of online video…every single day.

Is this really a surprising statistic? Whether you’re killing time watching videos of Bichon Frise puppies, catching up on last night’s NBA highlights, or binging your new favorite Netflix show, people have more reasons and more platforms than ever to engage with videos over an internet connection. It’s not just something people do at the end of the day—thanks to the rise in mobile video consumption, we watch videos waiting in the coffee line, on the subway, while watching TV (a growing trend called “two-screening” that is popular amongst millennials), and, of course, while sitting on the porcelain throne (don’t lie, we know you’re guilty of this—we’re guilty of it, too).

Video, whether it’s accompanied by audio or not, is an incredibly digestible and accessible form of media on a variety of platforms. Plus, there’s nothing like watching a live video to transport you to anywhere you want to go on the planet.

There are approximately 123 million IPTV subscribers around the world.

Nearly 47 million people subscribe to Netflix in the US alone, with over 47 percent of those subscribers coming from outside the States. This is just a fraction of the entire IPTV picture, with more and more people all over the world turning to IPTV solutions for video on demand content, breaking news coverage, and live entertainment and sporting events.

IPTV subscribership is rising at a rate of 12 percent per year.

With many traditional TV companies offering new IPTV platforms (i.e. HBO NOW, FOX NOW, The ESPN app), IPTV subscribership is growing at a healthy rate because it meets one single requirement of consumers today: it gives people the content they want, when and where they want it, on any desktop or mobile device.

This increase in IPTV subscribership has naturally led to a steep decline in traditional TV subscriptions. Overall, satellite and cable subscriptions are declining at a rate of nearly 2 percent per fiscal quarter, and the decline is much more drastic for some individual cable channels than others — in November of 2016 alone, ESPN lost a whopping 621,000 cable subscribers, and are on pace to lose 15 million total subscribers between 2012 and 2017.

In a world where the internet is king, consumers don’t sit around at home to wait for their favorite cable show at 8 p.m. anymore—they stream it through IPTV platforms anytime, any place they desire.

Originally published at setplex.com

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Rewards and recognition 2.0: What does it comprise of?

Employee recognition occurs when a manager or a peer recognizes a person’s efforts and/or achievements inside an organization. According to Bersin by Deloitte, 83 percent of organizations suffer from a lack of [employee] “recognition,” while just 17 percent of employees think their managers know how to recognize them properly.

While employee expectations of appreciation and recognition are nothing new, the manner in which recognition is offered must adapt to match the demands of the incoming workforce. By 2020, Millennials made up half of the global workforce, as they are more accustomed to receiving fast, frequent, and personalized feedback.

Communication between 9 a.m. and 5 p.m. is blurring as digital media allows for real-time communication to occur anywhere, at any time, and Millenials demand an ‘always-on’ communication loop. This generation’s usage of technology and connection with the digital environment clearly distinguishes them from earlier generations of employees. Managers have increased pressure to communicate and recognize success as a result of their drive to continued learning, ambition, and desire to rise quickly ahead within an organization.

Millennials have transformed the face of the workforce and will continue to do so, bringing new expectations to organizations. As a result, managers will need to broaden the range of recognition options accessible to them in order to come up with new methods to show their appreciation for their staff. While managers will be responsible for setting the bar for employee appreciation, it is HR’s responsibility to offer the systems that enable and support this process. 

The Value of Rewards to Humans

Rewarding someone for a job well done is not a novel notion. Whether it’s mythical stories about God’s blessings or historical ones about the role of olive branches in the Olympics, if you think about it, they were all begun in order to appreciate something that exceeded expectations. The industrial revolution, however, legitimized the approach to employee incentives and recognition programs. When and where did workplace recognition begin? What was early workplace recognition like back then? Giving gifts and tokens of appreciation were the basis of recognition. Managers are guilty of piling on unwanted presents such as showpieces to employees as rewards. 

Top Obstacles to Your Reward and Recognition Efforts

• By manually awarding and recognizing employees, there is a lack of
• A generic incentives scheme that does not meet the demands of your firm.
• Rewards and recognition are not given out on a regular and timely basis.
• Appreciation is restricted to a subset of the workforce.
• Ignoring the importance of a suitable reward and recognition platform

Why are traditional practices making the process boring and pushing it towards a slow death?

• A command-and-control strategy compelled all employees, whether they wanted to or not, to engage in programs.
• Because they were organizationally motivated, supervisors who were typically in charge of rewarding people had no idea what the employee was up to most of the time.
• Individuals who were not part of a bigger group were not inspired or motivated by impersonal communications.
• Generic incentives were not appealing to everyone. At the end of the day, one size does not fit all.
• Programs frequently felt inauthentic and dull due to the system’s repetitious nature.

Rewards and Recognition 2.0 – What Should it Comprise Of?

• Know Your Employee Needs: A rewards and recognition program’s primary goal is to make employees happy. So, the first thing you should think about is determining what makes your staff happy.

Every developing R&R program will need to do a preliminary study. It will aid in the development of a personalized program to meet the interests and needs of employees, increasing the program’s chances of success.

• Determine The Eligibility Criteria, And Award Frequency

Once your workers understand what might lead to awards and recognition, it’s time to inform them about who is qualified for it.

At the same time, you must ensure that the frequency of the incentives is defined, for example, weekly, monthly, or annual, etc. According to research, 71% of highly engaged employees work in firms that acknowledge the staff at least once a month. 

Here are some things to think about while deciding on the frequency of awards for a department.

• Do you have adequate departmental finances to meet the awards’ costs?
• Are the number of employees engaging in the program insufficient to make the program viable?
• Is it possible for your staff to share an award title at the same time? Or will it devalue the honor?
• Is the department running any other ongoing recognition programs?

• Fix The Criteria Of Winning

You can deal with it in two steps. First, select how the candidates will be brought into the spotlight. Who will make the decision? Will you implement a nomination system? If yes, decide who can and when they can nominate. Consider filling out a nomination form here.

Second, you must decide how you will choose a winner from the pool of nominated individuals. Combining manager and peer-to-peer recognition can be the most successful. 

• Building a culture of Peer-to-Peer Recognition program:

A peer-to-peer appreciation program provides an ideal chance to foster a culture of enhanced communication in the workplace. Overall, it assists a corporation in valuing everyone’s input.

A good peer recognition program may be advantageous in a variety of ways:

Improved working connections.

Enhances overall team morale.

Increases self-esteem and confidence. 

• Personalized Rewards:

The “one-size-fits-all” approach to personalized rewards is no longer effective for your staff these days. A custom-made award has a long-lasting effect on the receiver’s psyche. When you go out of your way to personalize your award, it establishes a bond between the receiver and the giver. 

• Make it user engaging:

The user interface of the R&R software should be straightforward, fluid, and easy to use. Because the application will be used by everyone in the firm, there should be no complex processes.

The application should be enjoyable and simple to use. Gamification in the R&R module can increase involvement by allowing workers to trade incentives or appreciation, establish an internal scoreboard, allocate points, and so on.

 

Here are a few ideas for employee appreciation that will make them feel all warm and joyful on the inside. Check these ideas out:

Gift of Gratitude: Everyone wants to be appreciated, and the effect of a spoken or digital “thank you” is unrivaled by any other form.

Anniversaries and Birthdays: On their day, you must make them feel special. And a cake and a digital “Happy Birthday” wish never fail to make your staff feel appreciated.

Personalized Note: Digital badges with a note are a very personal kind of acknowledgment that any employee would appreciate.

Hall Of Fame: Having a wall of fame in the office, or digitally showcased on a portal, where successes or achievements are exhibited for the entire workforce to view is the perfect way to top off the employee appreciation cake.

Celebrate Work Anniversaries: Employee milestones, like work anniversaries, are a terrific opportunity to show your appreciation.

Performance-based Recognition: Performance-based awards have their allure, and they have long proven to be a fascinating source of recognition.

Acknowledge Non-Work Achievements: You must constantly make an effort to recognize employees’ outside-work-related accomplishments. 

The Rewards & Recognition programs should constantly be updated to keep up with the time and employee expectations. Rewards are perceived differently by different people and so it is important to explore and execute what works.

Go up and beyond the conventional reward systems and experiment with new technologies and tools to drive appreciation at the workplace.

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5 Ways How VR Will Impact Education Process Soon

The rapid development of technology could not pass the educational process. And, while virtual reality (VR) technologies are not new to most people, they have only recently been used in the educational sector. What do you know about the impact of virtual reality on education?

People’s attention has been drawn to online education and interactive tools that can make learning more accessible, visible, and efficient due to the pandemic. Due to a lack of research data, many students who were self-educating were forced to seek writing assistance or buy dissertation online.

Virtual reality (VR) has evolved into an effective tool, allowing millions of students to better educate themselves even during a lockdown.

VR technologies have long been a part of daily life as well as professional human activity. Their integration into education is still negligible. Nonetheless, everything could change very soon. There are several significant reasons for this:

• Lowering the cost of technical equipment. Prices for modern VR devices designed for home and professional use have dropped significantly in recent years, making them more affordable.
• Increased investment in VR. In 2020, the global VR market was estimated to be worth USD 15.81 billion. From 2021 to 2028, it is expected to grow at a compound annual growth rate of 18%.
• Increased competition. In the European market, there are already over 300 VR companies, including market giants HTC, Microsoft, Samsung, Sony, and Oculus, which create fierce competition and produce useful VR products.
• Application fields expansion. Although virtual reality has long since ceased to be just a game story, it is now being used in many industries, including the oil and gas industry, education, mechanical engineering, energy, etc.

VR learning grounds on immersive technologies. It allow users to better perceive and understand a specific phenomenon, model situations, etc. That is, in a matter of minutes, these technologies immerse students in the required environment.

Here are the main advantages of VR use in education:

Clarity

A student can use virtual reality to examine objects and processes that are impossible or extremely difficult to trace in the real world. For example, anatomical features of the human body and the operation of complex mechanisms such as space flights, trips to different epochs, etc.

You will no longer wonder, “Can I pay someone to do my homework?” because VR allows you to get the most detailed look at the subject under study, eliminating the need for additional assistance.

Concentration

External factors have little impact on students in the virtual world. As a result, they can concentrate more on the cognitive process.

Involvement

The training scenario can be precisely programmed and tracked. Students can conduct chemical experiments, view historical events, and solve problems in a more captivating and understandable game format.

Safety

Students can perform complex operations in virtual reality without risking their lives. No matter how dangerous the experiment is, the consequences will not harm him or his classmates.

Efficiency

Many people nowadays continue to ask themselves, “Who can write my paper for me?” Experiments revealed that the performance rate of VR technologies is significantly higher than that of traditional learning methods. It reduces the number of search queries by providing students with the most comprehensive data for their research papers.

Teachers use computer technology in the modern educational process, in addition to textbooks, because this format of submitting information is more interesting and understandable for today’s generation of schoolchildren.

Heavy books replacement

VR technology aids in the retention of information and reduces the need for it to be repeated. Information is presented in classrooms using special glasses or classroom technologies.

Provision of exhaustive information

VR will help students learn more about complex subjects. For example, the teacher will no longer need to explain how the lungs appear outside and inside. Students will be able to see everything with their own eyes.

New education programs

VR based education programs will help students and teachers achieve better results.

Appearance Of A Shared Content-Base

A content base will allow teachers to create their own lessons while also utilizing the work of other teachers.

Increase In-Home Use

VR technologies promote remote learning and make it more accessible to all. They significantly increase the level of immersion in the material, resulting in students wanting to use it more frequently at home.

The next big thing in education is not technology but rather a teacher’s decision to push ahead and incorporate VR technologies into the classroom. The global goal should be to make knowledge available, accessible, and affordable to all people on Earth.

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