Inspiration
In both our society and personal lives, we see that employees of all backgrounds have one issue; a lack of satisfaction. People are condemned and burdened by the work, and feel that they are not getting a fair say in their company decisions, and are not being recognized for their work. To increase employee engagement and satisfaction, we felt that an app that allows executives to interact with the views of their employees would be a great solution. Thus, we created ManagE. It is envisioned to be a platform which considers employees and executives as equals, and fabricates an open environment for all employees to discuss their issues on recent company decisions, current events, and issues.
What it does
Our web app is a platform where employees and employers can communicate regarding specific company decisions. While promoting discussion, the app also keeps the anonymity of those who are conveying their opinions. In many companies, discussions sometimes turn into debates and criticisms. In fact, some employees are fired just because they voice their opinion. This situation can be observed in the newest of startups, to successfully established businesses such as Google. Similar to how votes are measured without collecting the name of a voter, our app displays the opinions of employees within a company while keeping the anonymity and privacy of those employees. Each employee has a username and password that they register for authentication purposes. The username is kept private to that employee himself/herself and the employer does not know whether that employee is registered or not. The purpose and main functionality of this app is to promote honest discussions and, at the same time, prevent conflict, criticism, or other unfavorable consequences for those voicing their opinions. Though free speech is a basic natural right provided to us by the U.S. Constitution, our app is one of several developments that assist in protecting that free speech.
How we built it
ManagE used a variety of aspects, including a dynamic back-end and a multitude of static pages. For the back-end, we used Django, due to our expertise in Python. The front-end was mainly HTML, CSS, and JavaScript, however, to create the different features of our website, we required more than the simple JavaScript. We needed a place to store every employee's messages. This is why we used ScaleDrone, a javascript API for messaging. It has a built-in database, and dynamic storage.
Challenges we ran into
The two main aspects of programming this app were programming the front-end and the back-end of our website. Some technical difficulties we faced while programming this web app were issues with javascript and jQuery, along with accessing our ScaleDrone messages database. As these were new programs and tools for us, we struggled to smoothly implement them into our web app. Being able to minimize the amount of files and increasing efficiency with these tools was also quite a struggle, due to their differing characteristics. We also faced technical difficulties programming the back-end. Link routing and database implementation were some of the issues. However, the greatest issue was understanding the framework we implemented for back-end and configuring the back-end to suit our purposes. We tackled these difficulties by surfing online resources along with implementing our own troubleshooting skills.
Accomplishments that we're proud of
Some accomplishments we are proud of are being able to implement such a broad idea in a short amount of time. Along with that, we were able to use new frameworks, APIs, and languages, which proved to be a great accomplishment.
What's next for ManagE
An improvement that we would definitely like to implement in a 2.0 version of our app is a feature for executives, where they can quantify their employees’ discussions into data. For example, a feature that counts the amount of pro/con keywords in the employees’ discussions, and formulates a bar graph based on the occurrences of the keywords, proving whether or not the common consensus of a decision is positive or negative. Along with that, we would like to create a machine learning program that uses the discussions to check whether or not the employees will like a certain decision which will be made. For example, if a new decision has been made by executives, and they want to know what the common consensus most likely will be, they can run the decision through our feature. It will analyze the decision, and formulate a possible decision of if the majority will be pro or con. This can save companies both time and resources before they finalize their decisions, and possibly decrease employee satisfaction.
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