What Are The Causes Of WeWork Company Bankruptcies?

Crisis management: how important is social media in a crisis?

Hi,

Welcome to my #2 blog post! I hope you enjoyed my previous post in which I wrote about creating your brand image and identity through social media. :)

This week, we’ll refer to crisis management. Crisis management is a part of public relations and it’s a process of dealing with some emergency situation. An important part of dealing with the crisis is social media.

Actually, when you think about it, many crises occur because organizations/companies don’t respond to the negative reviews and comments that people leave them on their social media accounts. I certainly think that a marketing team of a corporation thinks that it’s not a big deal when someone writes a rude comment about the products and services the corporation provides, so they do nothing regarding that question. And before they realize, they’re a step forward into downfall.

One good example of how to provide a customer service in an emergency is the situation when Sephora handled a crisis with the singer SZA. In April 2019, SZA tweeted that a Sephora employee called the security on her to stop her from stealing. She gained a lot of support, and people started tweeting how Sephora employees are rude and racist. Then, the official Sephora profile on twitter answered SZA’s tweet, and they let her know they are doing everything they can at the moment in order to clear the situation. A month later, Sephora posted on Facebook that all stores will be closed for an hour, because of a training of diversity. Clearly, SZA’s tweet encouraged whole Sephora’s team to do something about the customer’s service, which was, as we can see, terrible.

Sephora handled this situation pretty well, and they did the crucial things everyone needs to do, in order to get out of a crisis:

1. Value the customers’ comment and give them a feedback ASAP,

2. Imply that you’ll fix the situation ASAP;

3. Post about further steps taken in order to improve the customer service and satisfy every individual who comes into the store.

If every brand checked their social media multiple times a day, they would be able to prevent crises. With social media, “The customer is always right” upgraded to a new level. As a customer, if I’m not lazy to criticize a brand, then the brand should not be lazy to respond to me and give me feedback what will they do to improve the things I criticise.

After all, we all just look for some juciy drama on the Internet. And if we can’t find it, we create it ourselves. And companies should be aware of that!

References: 

“3 great examples of crisis management on social media” https://prconsultancy.org/3-great-examples-of-crisis-management-on-social-media/

Top 10 Data Science Project Ideas For Beginners - 2021

If you are an aspiring data scientist, then it is mandatory to involve in live projects to hone up your skills. These projects will help you to brush up your knowledge on knowledge and skills and boost up your career path. Now, if you write about those live projects on your resume, then there is a very good chance that you land up with your dream job on data science. But to be a top-notch data science engineer, it is essential to work on various projects. For this, it is important to know the best project ideas which you can leverage further on your CV.

Start Working on Live Projects to Build your Data Science Career

To get a sound idea for data science projects, you should be more concerned about it rather than it’s implementation. Because of this, we have come up with the best ideas for you. Here we have enlisted the top 10 project ideas that can shape your future in the world of data science. But to begin such programs or live projects, you need to have a good understanding of Python and R languages.

1. Credit Card Fraud Detection Mechanism

This project requires knowledge of ML and R programming. This project mainly deals with various algorithms that you can get familiar with once you start doing your applied machine learning course. These algorithms mainly cover Logistic Regression, Artificial Neural Networks, Gradient Boosting Classifiers, etc. From the record of the Credit Card transactions, you can surely be able to differentiate between fraudulent and genuine data. After that, you can draw various models and use the performance curve to understand the behavior.

This project involves the Credit Card transaction datasets that give a pure blend of fraudulent as well as non-fraudulent transactions. It implements the machine learning algorithm using which you can easily detect the fraudulent transaction. Also, you will understand how to utilize the machine learning algorithm for classification.

2. Customer Segmentation :

It is another such intriguing data science project where you need to use your machine learning skills. This is basically an application of unsupervised learning where you need to use clustering to find out the targeted user base. Customers are segregated on the basis of various human traits such as age, gender, interests, and habit. Implementation of K-means clustering will help to visualize gender as well as different age distribution. Also, it helps to analyze annual income and spending ideas.

Here the companies deal with segregating various groups of people on the basis of the behavior. If you work on the project, you will understand K means clustering. It is one of the best methods to know the clustering of the unlabeled datasets. Through this platform, companies get a clear understanding of the customers and what are their basic requirements. In this project, you need to work with the data that correlates with the economic scenario, geographical boundaries, demographics, as well as behavioral aspects.

3. Movie Recommendation System : 

This data science project can be rewarding since it uses R language to build a movie recommendation system with machine learning. The Recommendation system will help the user with suggestions and there will be a filtering process using which you can determine the preference of the user and the kind of thing they browse. Suppose there are two persons A and B and they both like C and D movies. This message will automatically get reflected. Also, this will engage the customers to a considerable extent.

It gives the user various suggestions on the basis of the browsing history and various preferences. There are basically two kinds of recommendation available-content based and collaborative recommendation. This project revolves around the collaborative filtering recommendation methodology. It tells you on the basis of the browsing history of various people.

4. Fake News : 

It is very difficult to find out how an article might deceive you mostly for social media users. So, is it possible to build a prototype to find out the credibility of particular news? This is a major question but thanks to the data science professionals of some of the major universities to answer the problem.  They begin with the major focus of the fake news of clickbait. In order to build a classifier, they extracted data from the news that is published on Opensource. It is used to preprocess articles for the content-based work with the help of national language processing. The team came up with a unique machine learning model to segregate news articles and build a web application to work as the front end.

The main objective is to set up a machine learning model that provides you with the correct news since there is much fake news available on social media. You can use TfidfVectorizer and Passive-Aggressive classifier to prepare a top-notch model. TF frequency tells the number of times a particular word is displayed in the document. Inverse Document Frequency tells you the significance of a word on the basis of which it is available on several contents. Therefore, it is important to know how it works.

A TfidfVectorizer helps in analyzing a gamut of documents.

After analyzing, it makes a TF-IDF matrix.

A passive-aggressive Classifier tells you whether the classification outcome is viable. However, it changes if the outcome swings in the opposite direction.

Now, you can build a machine learning model if you have such good project ideas.

5. Color Detection :

It might have happened that you don’t remember the name of the color even after seeing a particular object. There is an ample number of colors that are totally based on the RGB color values but you can hardly remember any. Therefore, this data science project will deal with the building of an interactive app that will find the chosen color from the available options. In order to enable this, there should be a detailed level of data for all the available colors. This will help you to find out which color will work for the selected range of color values.

In this project, you will require Python. You will utilize this language in creating an application that will tell you the name of the color. For this, there is a data file that comes with color names and values. Then it will be utilized to evaluate the distance from each color and find out the shortest one. Colors are segregated into red, green, and blue. Now the PC will analyze the range of the colors varying from 0 to 255. There are a plethora of colors available and in the dataset, you need to align each color value with the corresponding names. It requires a dataset that comprises RGB values as per the names.  

6. Driver Drowsiness Detection :

In order to perform training and test data, researchers have come up with a Drowsiness Test which uses the Real Life Drowsiness dataset in order to detect the multi-stage drowsiness. The objective is to find out the extreme and discernible cases related to drowsiness using data science Skill. However, it permits the system to find out the softer signals of drowsiness. After that, comes the feature extraction which needs developing a classification model.

Since overnight driving is really a difficult task and leads to varied problems, the driver gets drowsy and feels quite sleepy while driving. This project helps to detect the time when the driver gets lazy and falls asleep. It produces an alarming sound as soon as it detects it. It implements a unique deep learning model to determine whether the driver is awake or not. This comes with a parameter to find out how long we stay awake. If the score is raised above the threshold value, then the alarm rings up. Now, you can easily be able to get the related dataset and Source Code.

7. Gender and Age Detection : 

This is basically a computer vision and machine learning project that implements convolutional neural networks or CNN. The main objective is to find out the gender and age of a person using a single image of the face. In this data science project, you can segregate gender as male or female. After that, you can classify the age on the basis of various ranges like 0-2, 4-6, 15-20, and many more. Because of different factors such as makeup, lighting, etc, it is very difficult to recognize gender and age forms a particular image. Due to this, the project implements a classification model instead of regression.

For the purpose of face detection, you will require a .pb file since this is a protobuf file. It is capable of holding the graph definition and the trained weights of the model. A .pb file is used to hold the protobuf in a binary format. However, the .pbtxt extension is used to hold this in the text format. In order to detect the gender, the .prototxt file is used to find out the network configuration. The .caffemodel file is used here to denote the internal states of various parameters.

8. Prediction Of The Forest Fire : 

Both forests, as well as the wildfire, ignites a state of emergency and health disasters in modern times. These disasters can hamper the ecosystem and this can cause too much money. Also, a huge infrastructure is required to deal with such issues. Therefore, using the K-means clustering you can easily be able to detect the forest fire hotspots and the disastrous effect of this nature’s fury. With this, it can cause faster resource allocation and the quick response. The meteorological data can be used to determine the seasons during the forest fires that are more frequent. Also, you can determine the weather conditions and climatic change that can reduce them and bring sustainable weather.

9. Effect of Climate Change on Global Food Supply :

Climatic change seems to affect various parts of the world. As a result, people residing in those areas are also under the wrath of such climatic change. The project mainly deals with the impact the climatic change is having and its effect on the entire food production. Main motive of the project is to determine the adverse effect of the climate on the production of crops. The project ideas mainly revolve around the impact of temperature and the rainfall along with the diversified cause of carbon dioxide on the growth of the plants. This project mainly focuses on the various data visualization techniques and different data comparisons will be drawn to find out the yield in various regions.

10. Chatbot-Best After the Data Science Online Training :

This is one of the famous projects done by the most aspiring data science professionals. It plays an important role in the business. They are used to give better services with very little manpower. In this project, you will see the deep learning techniques to talk with customers and can implement those using Python. There are basically two types of chatbots available. One deals with the domain which is used to solve a particular issue and the other one is an open domain chatbot. The second one you can use to ask various types of questions. Due to this, it requires a lot of data to store.

“ Upskill Yourself Through Online Data Science Courses and Become a Professional ”

The projects discussed in this technical article covers all the major Data Science projects which you need to do if you are a budding data science professional. But before that, you need to have a good grasp on various programming languages like Python and R. If you do the data science online tutorials, then these projects will be a cakewalk for you. Remember, one thing these small steps will make the large blocks so that you can rule the world of data science.. So, go ahead and participate in these live projects to gain relevant experience and confidence.

How does Cloud Computing benefit businesses?

There is a good chance you already use cloud storage to store the photos from your smartphone or to run software on your laptop. In the UK, SMEs are now gravitating towards cloud computing rapidly thanks to the fact that it provides a relatively low-cost solution to a problem whilst offering massive amounts of flexibility.

Cloud computing allows a type of flexibility that we have never enjoyed before. It also allows businesses to improve their services to work far more efficiently and educate employees on the benefits of Cloud Computing.

The Cloud will play an active part in helping you achieve many of your business goals as it can be a powerful tool and expansive in a way that seemingly knows no bounds. It can also offer cost-effective solutions and allow smaller businesses to expand without breaking the bank.

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“Solving a problem is hard enough; it gets that much harder if you’ve decided beforehand it can’t be done”

Steven D. Levitt & Stephen J. Dubner

How to be more productive?

1. Set Clear Goals: Define what you want to achieve and break it down into smaller, achievable tasks. This helps you stay focused and motivated.

2. Prioritize Tasks: Identify the most important tasks and tackle them first. Use techniques like the Eisenhower Matrix (categorizing tasks based on urgency and importance) to prioritize effectively.

3. Manage Time Wisely: Plan your day and allocate specific time slots for different tasks. Avoid multitasking as it can lead to decreased productivity. Use techniques like Pomodoro Technique (working in blocks of time with short breaks) to stay focused.

4. Minimize Distractions: Identify and eliminate any distractions that hinder your productivity, such as notifications, social media, or cluttered workspaces. Consider using productivity tools or apps to help you stay focused.

5. Take Regular Breaks: Breaks are essential for maintaining focus and preventing burnout. Incorporate short breaks throughout your workday to recharge and rejuvenate.

6. Delegate and Outsource: Learn to delegate tasks that can be handled by others. This frees up your time to focus on more important or high-value tasks.

7. Maintain a Healthy Lifestyle: Ensure you get enough sleep, exercise, and eat nutrient-rich meals. Taking care of your physical and mental well-being enhances your productivity.

8. Learn to Say No: Avoid overcommitting yourself. Learn to say no to tasks or projects that don't align with your goals or priorities.

9. Continuously Improve: Seek ways to enhance your skills and knowledge. Constant learning and growth help you become more efficient and competent in your work.

On this episode of Now & Then, “Democracy Is In the Mail,” Heather Cox Richardson and Joanne Freeman talk about the development of the post office in American culture. They explain why the Framers believed so deeply in a government-backed mail service, trace how Western expansion changed the culture and organizational structure of the Post Office Department, and recount the 1970 postal strike and the impact of the resultant Postal Reorganization Plan. How has the mail bolstered democracy? Should the postal bureaucracy be run like a public utility or a business? And can the Postal Service withstand the current push for privatization?

Why does due diligence matter?

Due diligence in business is the effort or process of gathering and analyzing information about a company before making a decision or performing a transaction involving that company. Due to the fact that no two organizations or corporations are alike, it is critical to do due diligence in order to get any information connected to the company or its assets. 

Why is due diligence important to you?

You may believe that due diligence just serves one side, the buyer. However, it helps both parties, i.e., buyers and sellers.

Due diligence provides a buyer with all of the information they need to make a purchase and gives them peace of mind that they are making the proper decision. The data contains information about existing consumers, collaborations with other businesses, and any potential risks that the merging firm may face.

Due diligence, from the standpoint of a seller, assists the owner in learning more about their own firm, such as financial stability, and will also give information on why their market worth is low. Furthermore, it assists the owner in understanding their firm from the buyer’s point of view.

What does the due diligence report include? 

The due diligence report is divided into five major categories. 

Ø  Legal reviews: Due diligence assists in evaluating whether or not the company with whom we intend to form a partnership has any liabilities. And, depending on the size of the company, the due diligence report clarifies whether or not there is any potential danger.

Ø  Environmental Considerations: In the case of some companies, there may be some environmental risks associated with the business. In this sort of scenario, due diligence examines all of the risks and explains how they may influence the firm in the present or in the future.

Ø  Financial information: The majority of firms concentrated on financial due diligence, reviewing and verifying all financial data. They check whether all of the data given is up-to-date and accurate or not.

 Ø  Business Sustainability: Cash flow management and long-term business sustainability are two critical components of due diligence. Based on these components and sales data from previous years, buyers will be able to decide if the investment is profitable.

Ø  IT Capabilities: Identifying the company’s existing security threats and other IT-related issues fall under this area. 

Due diligence will always be a vital aspect of running a business, especially whether forming a partnership or purchasing a firm. So, whether you are a buyer or a seller, due diligence is essential for both sides.

Top causes that lead companies to go bankrupt

Excessive Debt:

High levels of debt, whether due to overleveraging, poor debt management, or economic downturns affecting the ability to service debt, can lead to financial instability and bankruptcy. Companies that struggle to meet interest and principal payments may find themselves in a precarious financial position.

Poor Financial Management:

Ineffective financial management practices, including inadequate budgeting, inefficient resource allocation, and a lack of strategic financial planning, can lead to poor financial performance. Without proper financial oversight, companies may struggle to remain competitive and profitable.

Market Changes and Economic Downturns:

External factors such as economic recessions, shifts in market demand, or changes in consumer behavior can significantly impact a company's revenue and profitability. Companies that fail to adapt to changing market conditions may find it challenging to sustain operations and meet financial obligations.

Operational Inefficiencies:

Inefficient operational practices, high production costs, and poor supply chain management can erode a company's profit margins. Operational inefficiencies can lead to reduced competitiveness and financial strain, ultimately contributing to bankruptcy.

Lack of Innovation and Adaptability:

Companies that fail to innovate, keep up with technological advancements, or adapt to evolving industry trends risk becoming obsolete. Lack of innovation can result in declining market share, reduced revenue, and ultimately financial distress.

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How to select the best Project Management Software

Project Management Software has become a must for all businesses nowadays. Project management entails determining the strategy and acquiring the necessary people and resources to plan, execute, and deliver a project on schedule and within budget. The program has been widely utilized in a variety of industries, including IT, construction, architecture, sales and marketing, surveying, and so on, for efficiently and successfully managing projects. However, it is important for you to have a clear understanding on how to pick the best project portfolio management software.

Why do you need a project management tool?

The project team, which consists of the project manager and team members, is involved in the management process. To increase efficiency and carry out the entire management process, they employ apps and tools to evaluate, plan, schedule, track, and manage projects. Your organization may use the program to keep projects up to date, stay up to date, and manage data. Just keep in mind that the software can only help the project team succeed; everyone must contribute to each job and to anything else is required. If you work with the improper blueprints, you won’t be able to complete a job effectively.

How to select a project management software

In today’s corporate world, project management has become increasingly important. The finest Project Portfolio Management Software is one that fulfills or matches the project’s needs for completion. These vital functions should be performed by the primary aspects of selecting software:

Priorities for Project Management

It’s helpful to have a better grasp of project management tasks from time to time when reviewing business software. This aids in establishing whether the program is capable of resolving any issues your company may have. Applying existing management techniques to project management software will aid in identifying how the program may be used to solve an issue. Breakdowns of what a project requires can also show how projects and software interact with one another.

Assess Future Project Management Requirements

While it’s tough to forecast how software will evolve over time, it is feasible to comprehend the program’s adaptability. A company’s ability to grow is aided by adaptable software. Simple-to-use software may or may not be able to adapt to a company’s changing demands as it expands. The more adaptable the software, the more alternatives a corporation will have to deal with a variety of scenarios. Without degrading current projects, a successful Project Management solution accepts change and meets changing business expectations.

Accounting Software Integration

A project management software’s capacity to synchronize company data with other software is a critical component. Because a firm may be utilizing an existing application and would like it to be synced to their preferred software, a program that can combine other software systems to function together is much better. In fact, choosing software that can interface with other programs can save money by reducing data setup time.

Relationship between the software provider and the customer

Both the software vendor and the client must build a mutually helpful relationship. When choosing project management software, it’s important to evaluate the software vendor’s responsiveness and competence, as well as its support for the purpose of serving. The organization or corporation should also note how keen the vendor and support are to assist when queries or difficulties emerge, as well as how quickly they respond. The seller should take an active role in assisting their customers.

If a corporation is currently utilizing a program and wishes to transfer to a new one, they should figure out how such a transition will be handled and whether such actions will be performed. When a corporation wants to move data from its present program to the chosen software, the changeover might be costly. As a result, such a corporation should assess how much effort is required to migrate to new software.

Now you have a clear understanding on how to select the best Project Management Software. Keep these options in your mind and invest your money on the most perfect tool available out there. Then you can streamline your projects and end up with receiving the best returns coming on your way.