Automation is essential for data management because of its efficiency and accuracy. Any time a person is tasked with manual data entry, there is a significant risk of error. That risk increases exponentially as the data volume increases. These are the three basic steps to building and executing a project plan to incorporate automation into your daily routines.
- Identify
The first step towards automation is to identify the data sets that require regular manual manipulation as well as the databases or software systems where the information resides. Processes could be either data entry/transfer (e.g., entering employee demographic information) or the processing and interpretation of data (e.g., share usage projection). This is the time to really brainstorm. Every single process you do can go on your list; each process may include several steps that should be broken down into individual opportunities for automation. Take your list and create a spreadsheet with a list of each process, where the data originates, where it needs to be transferred to, and what departments or outside service providers are involved.
Take time at this step to get to know each of the database or software systems that your data touches because this knowledge will carry forward to each piece of automation you build. Drill down each system’s capabilities for formatting output of data and accepting data as an upload. If you are manipulating data for analysis, it may be possible to build data output reports that either reduces the manual processes for analyses or provides the data in a format that requires no further manipulation. When starting your automation project plan, you are only looking to understand the potential from each of your data systems; you don’t need to detail the entire business specification at this point.
- Prioritize and Build
Once you have identified which data processes are candidates for automation, it’s time to prioritize. A good place to start is to eliminate the processes that require data output formats that your systems can’t accommodate at this time. These items can take a different route as topics to approach with the database architects, whether they are internal or external contributors. Rate the remaining processes on how easy each is to automate as well as how significant the process is. Significance is the more difficult to define because it could mean processes that impact the highest volume of data, represent the highest risk of error, or are components of the most visible data outputs. This helps when determining which pieces of automation to tackle first.
Once you’ve established your project priorities, build your automation. You don’t need to tackle projects one at a time. You may find that some pieces may build on each other because they use the same original data. Additionally, you may be able to oversee more than one automation project simultaneously if the process requires time commitments from separate groups.
- Bust
The final step for automating a process is to break the automation. Well, at least try your hardest to break it. Take each piece of the automation and think of as many situations as you can where data will feed into or come out of that process, even if it’s not what the process was originally intended for. Don’t limit yourself to using correct data, either. It’s important to know what will happen if incorrect or incomplete data sets are used so that you can recognize these problems if or when they happen in the future. Remember, you may not be the only one using the process and it could be the platform for further automation in the future.
-Rachel
Tags: administration, automation, database, HR, IT, payroll, software
As a stock plan administrator, you should be running regular audits of the underlying data in your stock plan database. Regular plan share reconciliation can uncover transactional issues such as late reported terminations or exercises that were entered after the period-end. Most, if not all, stock plan administration software has some type of data check that can uncover incongruous data such as a termination date that is prior to a hire date or grants that have more exercised shares than vested shares. Both periodic plan share reconciliation and running the software’s built-in data check should absolutely be a part of your regular procedures. However, neither of these is a substitute for a periodic audit of underlying data.
Here are the top five additional data audits that you should complete on a regular basis:
1. Active employees
This is a fast check, and with the right IT team can be easily automated. Simply run all your current, active employees from each database (I recommend your HR, Payroll, and stock plans databases) and confirm that each has the same list. Do this audit for both the employee ID and the SSN or other identifier to help catch rehires who have accidently been assigned a new employee ID.
If your stock plan administration database stores the history, match up the new hire, termination, and rehire dates for employees in your database against the HR records. If your company has a policy that re-instates grants when the rehire takes place within a set period of time, then this check will be particularly important for catching changes in rehire date that could impact the status of grants.
2. Changes in employee status
Audit your employee records to confirm that changes in employee status reflect correctly in your stock plan administration database. This includes leaves of absence, changes from and to part-time, moving from employee to non-employee status, and any other changes that may impact eligibility for equity compensation. Most HR databases will record the current status of employees and transmit this information to at least the payroll department. If you are unable to do a full employee status history audit, then at a minimum check to see that the current status is accurate.
3. Fair market value
Hopefully, you (or your service provider) complete a daily verification of the share prices that are entered into your database as the fair market value for company’s shares. These values may be used to determine grant size, exercise price, ESPP purchase price, and income/tax amounts for transactions. In addition to your daily check, it is a good practice to do a periodic audit of the values in your stock plan database against two outside sources. Occasionally, important share prices such as the day’s high, low, or closing price are corrected after market close. If your daily confirmation takes place prior to the change, you will not know about it without this additional audit. Additionally, you should confirm that all sale prices for same-day sales as well as applicable ISO and ESPP sales fall between the high and low share price for the transaction date.
4. YTD supplemental income and social security paid
The year-to-date supplemental income and social security paid for your U.S. employees can impact the appropriate tax withholding amounts for their transactions. The best practice is for year-to-date supplemental income and social security tax amounts to be communicated automatically from your payroll database to your stock plan administration software. Regardless of whether or not your company has automated this data upload, a regular audit of these amounts can help uncover corrections made in payroll that either were not loaded to the stock plan administration software or were not corrected in a timely manner and data that is simply incorrect in the stock plan adminstration software. In addition to your regular audit of these amounts, you should have a process in place to catch transactions that are transmitted to payroll with a tax withholding rate that is either too high or too low based on the current payroll information.
5. Employee demographic fields
Your company should be tracking key employee demographics in the stock plan administration software. These may include department, work location, cost center, or other identifying factors. These fields must be accurate for your expense allocation, tax deductions, future cost projections, and most one-off reports that other departments may request.
Keep in mind that all of these data audits can be automated or incorporated into regular exchanges of data. Work with your service provider(s) and your IT to see what opportunities for automation you may be overlooking. Even if the automation simply alerts you to inconsistent data points, it can simplify your audit process. Remember, these pieces of data are the foundation for all the information that comes out of your stock plan administration software. Including these audits in your regular procedures will help you remove bad data before it shows up as an issue in your periodic reporting.
-Rachel
Tags: administration, audit, database, reconciliation