Dynamic security profile gives us the option to use a single person security profile & single data role with the additional help of Area of Responsibility to provide access of employees to the user based on the attributes like a business unit, department, etc.
Using the dynamic security profile is a recommended approach as this requires less maintenance compared to the security provided via traditional method based on security dimension. Especially helpful in the cases where the security must be provided based on location, department or business unit and there are tens and hundreds of these values.
Creating Dynamic Person Security Profile
In Functional Setup manager search for the task ‘Manage Person Security Profile’
Click on the ‘Create’ icon to create a new Person Security Profile
On the Create Person Security Profile page provide the name for the profile.
Under Custom Criteria check the checkbox ‘Secure by Custom Criteria’ and copy the below mentioned SQL in the SQL box and then click on the validate button to validate the sql. (Provide the responsibility type code which is used by you in your project, delivered code is HR_REP)
EXISTS(SELECT 1 FROM PER_ALL_ASSIGNMENTS_M ASG,PER_PERIODS_OF_SERVICE PS,PER_ASG_RESPONSIBILITIES RES WHERE ASG.ASSIGNMENT_TYPE IN(‘E’,’C’,’N’,’P’) AND ASG.EFFECTIVE_LATEST_CHANGE=’Y’ AND SYSDATE < ASG.EFFECTIVE_END_DATE AND PS.PERIOD_OF_SERVICE_ID=ASG.PERIOD_OF_SERVICE_ID AND (ASG.ASSIGNMENT_STATUS_TYPE IN (‘ACTIVE’,’SUSPENDED’) OR (ASG.ASSIGNMENT_STATUS_TYPE IN (‘INACTIVE’) AND NOT EXISTS (SELECT 1 FROM PER_ALL_ASSIGNMENTS_M EXASG WHERE EXASG.ASSIGNMENT_TYPE IN(‘E’,’C’,’N’,’P’) AND EXASG.EFFECTIVE_LATEST_CHANGE = ‘Y’ AND EXASG.PERSON_ID = ASG.PERSON_ID AND SYSDATE < EXASG.EFFECTIVE_END_DATE AND EXASG.ASSIGNMENT_STATUS_TYPE IN (‘ACTIVE’,’SUSPENDED’)) AND PS.ACTUAL_TERMINATION_DATE = (SELECT MAX(ALLPS.ACTUAL_TERMINATION_DATE) FROM PER_PERIODS_OF_SERVICE ALLPS WHERE ALLPS.PERSON_ID = ASG.PERSON_ID AND ALLPS.ACTUAL_TERMINATION_DATE IS NOT NULL))) AND SYSDATE BETWEEN RES.START_DATE AND NVL(RES.END_DATE,SYSDATE) AND ASG.PERSON_ID=&TABLE_ALIAS.PERSON_ID AND RES.PERSON_ID=(SELECT HRC_SESSION_UTIL.GET_USER_PERSONID FROM DUAL) AND RES.RESPONSIBILITY_TYPE=‘XX_HRM’AND ASG.BUSINESS_UNIT_ID=RES.BUSINESS_UNIT_ID)
Click on the Next button to preview the dynamic security profile.
Click Save and Close to create the dynamic person security profile.
Creating Data Role
In Functional Setup manager search for the task ‘Manage Data Role and Security Profiles’
On the Search page click on the ‘Create’ icon to create a new data role.
Enter the details in Data Role, Role Description and select an existing Job Role in most cases you will be building the data role on the delivered ‘Human Resource Specialist’ role. It is always advised to use a custom job role which is based on the delivered role because when you use custom job role you can add or remove the privileges from it whereas when you use the delivered job role then you cannot add or remove the privileges. (Privileges provides the access to the navigations)
Click OK on the warning if you get any.
On the create Data Role: Security Criteria page select the required values (In person security profile select the value created in the above step)
Click on review button then click on submit to save the page.
Upon submission the data role will be created and ready for our use. This can now be assigned to any person.
Assigning data role & Area of Responsibility to the user
Assign this Data Role to the user from Security Console.
SmartERP’s webinar, How Should Organizations Take Advantage of the Growing On-Demand “Gig-Economy?,” presented by the author of Thriving In The Gig Economy, Marion McGovern and Hans Bukow, Chief Strategy Office, SmartERP. Today’s workforce features increasingly flexible work situations while, also dealing with a shortage of timely needed skills. The current competitive landscape continues to demand more contingent workers, freelancers, contractors, and several other types of specialized on-demand “gig” workers. In this webinar on demand you will learn more about how to operate with emerging independent talent marketplaces. Our speakers also discuss capitalizing on the strategic use of high-value, skilled, contingent workers, how to procure, onboard, and manage them, while reducing risk and avoiding compliance issues for your organization.
The contingent workforce is growing rapidly. With independent contractors growing 40% in just ten years and some organizations dedicating upwards of 30 percent of their workforce pool to be independent contractors, the government is paying far more attention to how employers comply with the Fair Labor and Standards Act. The truth is, worker misclassification can hurt both workers and employers, although the regulations are in place to protect the individual worker. These are some of the consequences that both workers and employers face with worker misclassification:
Typically, employers pay a certain number of taxes as part of an employees payroll. These include social security, unemployment, and other taxes. In most cases, independent contractors take on these expenses in the form of self-employment tax which they pay directly to the government. It isn’t uncommon for a worker who is labeled as a contractor to be paid less than an employee and still be responsible for these additional costs.
Labor Rights Violations
The Fair Labor and Standards Act plus subsequent laws passed by Congress layout in fairly explicit detail precisely what worker protections must be followed. When it has been determined that those regulations haven’t been complied with, the government uses enforcement power, usually in the form of significant fines, to force compliance.
The government has the authority to levy stiff penalties against organizations found to be improperly classifying workers.
While each case can be different, fines can be assessed for a myriad of different violations. For example, for every worker found to be misclassified, there can be fines of $50 dollars for every W-2 form that wasn’t filed, 1.5% of wages plus interest, and 100 percent of the employers matching FICA contributions, plus others. If it was found that the misclassification was intentional, those fines can rise rapidly. Up to $1,000 dollars for every employee in criminal fines, 20% of wages and even jail time are a possibility for these more serious intentional infractions.
Other Legal Issues
Government regulators aren’t the only ones with the power to enforce these labor laws. Employees and independent contractors have the ability to bring their own legal complaints against employers and have sometimes seen staggering awards. In the well-known case of Uber drivers who were classified as independent contractors, a settlement was reached that awarded the drivers $100 million dollars. That settlement was later thrown out by a federal court who deemed the settlement figure too small.
How to Avoid Employee Misclassification
As shown above, there are penalties for employee misclassification regardless of whether or not it was intentional. That means that avoiding this mistake saves your organization time and money. That’s why it’s important to create an atmosphere of enhanced compliance and awareness from the top down, beginning during onboarding.
The Five Cs of Strategic Onboarding:
What can SmartERP’s Smart Talent Procurement do to help organizations?
Organizations want and need to make sure that the independent contract work being requested is going to be compliantly and correctly performed per the government’s and the organization’s own rules. Organizations should also perform some curation of their contracted workers since suppliers do not often fully qualify their workers or project work.
It’s up to the organization to make sure that:
The work their hiring managers are offering is truly classified as suitable for independent contractors – per national standards (IRS) and state/municipality standards.
If the work requested doesn’t qualify then how can it be modified or offered to vendors under a different compliant classification under some managed system?
The contingent worker being offered a position has all that’s needed to work at the organization, or business unit, or location, etc., that’s hiring them. For example, the worker needs to provide evidence that they have enough insurance or certifications to do the work.
The workers being hired to do the work are efficiently and compliantly onboarded as to save time, expense and to provide all with a more streamlined, less risky and efficient operational environment.
When your resources are spread across various staffing vendors, recruiting and selection can become a formidable and complicated task. To make it worse, each hiring manager can have different preferences and criteria, creating inconsistencies in hiring standards and potentially harming the quality and value of your hires. To fix this problem, the first thing your organization should do is streamline and consolidates all workforce requirements and criteria. By standardizing the requirements for all hiring managers, you can ensure that all your hires will meet your standards and expectations, and also allow you to maintain better control over the process.
Strengthen Your Talent Acquisition Team
In Bersin’s latest High Impact Talent Acquisition Study, Bersin found that talent acquisition (TA) is an important contributor to an organization’s success. Advancing your organization’s Talent acquisition capabilities require significant effort, investment, resources, and cultural change, but it also brings remarkable benefits from the enhanced business performance. Organizations with strong, high maturity TA functions reap 19% more revenue than organizations with low maturity TA. In terms of profit per employee, high maturity organizations can enjoy a 30% advantage over their low maturity counterparts.
Set Up A Straightforward Vendor Management System (VMS)
Next, set up a straightforward vendor management system that oversees and manages the selection process will help your organization pick top applicants. At the same time, it will also allow you to apply downward pressure on vendor markups to increase your negotiating power by increasing competition between vendors. One way to do this is by maintaining vigilance for vendor partiality and encouraging fair opportunity and competition.
Vendor favoritism encourages inefficiencies and increases costs. Being vigilant and installing tender process helps confirm that you will get fair market rates for all your workers. In turn, this will allow you to gain back some of that buying power by allowing you to have better control during renegotiations, and thus, better rates.
Both of these options will allow your organization to reduce the number of candidates and select top-quality vendors, thus enhancing worker quality. Furthermore, consolidating your requirements will grant HR access to important data that will allow them to help make better decisions. It will also help ensure that all compliance requirements are met and prevent misclassification of your contingent workers, which can result in monetary or non-monetary penalties by the government. Or worse, civil and criminal liabilities. The government can impose a variety of penalties on your organization, depending on whether you intentionally or unintentionally misclassified employees. Either way, automating your requirements and selection process can help you prevent any penalty.
This question is easier to answer through a demonstrative example than by a long description extending to multiple paragraphs. Take a look at the sample data shown below.
This is a screenshot taken from a python jupyter notebook view of the data frame obtained using pandas library. The data is arranged in rows and columns. Every column is one variable or data field and every row is one record. From now onwards, I will be adhering to terminologies aligned with machine learning (ML) as much as possible.
Here’s a question for you. Given a chance to pick a data field whose values are strongly related to values in one/more of the remaining fields, what will be your choice? Well, you got it right – “Chance of admit” and this is going to be the target data field, which is called a label. Now you have to pick one (more) field(s) from the remaining set, which you feel can be mapped to the label. The set of fields you selected are the features. Features are nothing but predictor variables for the label. Mind you, the predictors should not be interrelated in any way. So, the rule of thumb here is
Predictors – Independent variables; each predictor is independent of the others.
Target – Dependent variable
In a regression problem what you do is find a mathematical relationship between the features and the label. Once this relationship is established, then the value of the label can be predicted for any given set of values of features. The label will always be a continuous variable of numeric type. In this example, I have considered all the feature values as of type numeric, but in general, they can be of type ordinal/nominal/interval as well. A detailed discussion about the data type of feature variables is not intended to be a part of this blog.
There are several open source ML algorithms available to handle regression problems, starting from multiple linear regression to random forest to complex neural networks. They all work in different ways. The fundamental difference is, whilst linear regression mines for any linear relationship between the label and the features, other algorithms look out for non-linear relationships as well.
My sole focus in this blog will be on multiple linear regression (and its variants in subsequent episodes of this blog) as it is the simplest and therefore easiest to understand; it is also a good starting point for someone who wants a jump start in ML.
Multiple Linear Regression
To start with, I am picking GRE Score, University Rating, SOP, and Research as features. There’s no concrete reason as to why I picked these fields, I just picked it. For this set of features, I can write the equation for a regression model as
Chance_of_Admit = (a x GRE_Score) + (b x University_Rating) + (c x SOP) + (d x Research) + e
Where a, b, c, and d are the model parameters for the regression model generated. Now the question is how will you get the values of a, b, c, d, and e. You feed the data for both features and label into your ML algorithm and allow it to find the best values for the model parameters.
An example of how to perform this using python is shown below. To run this code you have to import the library statmodels.formula.api
Note that the best values for the model parameters are obtained by running the algorithm by calling the function ols(). The same can be displayed along with several other statistics by calling the function summary()
The statistics are shown in the above screenshot also contains information about the goodness of the model and the relevance of each feature to the model.
Now that you have the model created, you can use it to get the predictions from the model for the label. To run the model with some new data, I have created a dataset new data as shown below. Predictions from the model are obtained using predict() function
In this blog, I have not talked about data types and how to handle data of a type other than numeric. The blog also does not cover the topic of data preparation which can take you a long way in getting very good model performance. Details of the model statistics and improving the quality of the model through feature engineering are two more things that can go into the “Missing List”.
I omitted these topics intentionally for fear of deviating too much from what I really want to put in. But stay tuned, these will be covered in upcoming blogs.
There is a unique set of challenges and risks for all organizations
The advent of new employment protection laws and the rise of the freelance economy/”gig” worker has given rise to a significant number of penalties being levied against employers who misclassify their employees.
Determining whether a worker is an employee or an independent contractor is a necessary part of the hiring process, but if done improperly it can lead to a lot of potentially expensive problems. Here’s what you need to know about employee misclassification and what steps you can take to avoid it.
The “gig” worker is projected to increase to 43% by 2020
What is Worker Misclassification?
Worker misclassification is simply incorrectly identifying individual members of your workforce as either employees or independent contractors. While this can happen as a result of a mistake, the consequences can be real and very expensive, even if the action was not intentional. The first step to avoiding this mistake is to understand just exactly what makes each role unique, so this is what classifies a worker as an employee versus a contractor.
What is an Employee?
An employee-employer relationship is much more defined in the boundaries of the role. Traditionally, this is how most people have been employed. This means that the employer dictates:
The hourly or salaried rate of pay
How and when work is performed
Key performance indicators and quality standards
What is a Contractor?
The rise of the digital and distributed economy has given a noticeable rise to the number of contracts in the job market. A contractor has more flexibility in how they choose to carry out their role to achieve a stated goal. They should control:
Their rates of pay
Where and how the job is done
Increasing or decreasing the scope of work based on skill and ability to have a significant impact on the bottom line
Employer misclassification of employees as independent contractors is a widespread phenomenon in the United States. The Internal Revenue Service (IRS) estimates that employers have misclassified millions of workers nationally as independent contractors
Misclassification in the FedEx Business Model—a Case Study:
It is estimated that FedEx reduced their labor expense by as much as 40 percent by misclassifying drivers as independent contractors. For quite some time, FedEx has denied that their Ground and Home drivers are employees entitled to benefits and the right to unionize. By classifying drivers as independent contractors, FedEx was able to transfer operation costs onto its drivers, avoided paying Unemployment Insurance and Social Security taxes for the workers, and excluded drivers from FedEx’s health and pension plans.
The Federal Ninth Circuit Court of Appeals ruled that FedEx misclassified 2,300 workers in California and Oregon as independent contractors. The Kansas Supreme Court ruled that FedEx drivers are company employees, not independent contractors.
In this webinar recording, you’ll learn how Modern Supply Chain Management systems can meet the challenges of business for your organization, including new regulations, increased buyer expectations, shorter product lifecycles, fluctuations in demand, new market entrants, poor visibility of globalized supply chains and more.