Process Improvement – Quick Wins – Five actions that can quickly improve a process
A small improvement can go a long way. Not all process improvements have to be fundamental overhauls or redesigns. There are a number of things I have found that can be done quickly and immediately to improve a process or a report.
I swear by checklists. A simple list of what needs to be done during the process, when and by who. This could be to check that the monthly data has been downloaded on the right day, or that each spreadsheet page has been updated.
A checklist has two effects. Firstly, it gives the discipline to remind people what to do – following and ticking off a list makes it easy to remember everything. Secondly it gives visibility that everything has indeed been done – it is a completeness check for managers, stakeholders, and above all, auditors, to have confidence in the process.
I recently came across a process that required some standing data (mapping of accounts to cost centres) to be updated each month, the mapping being used in subsequent reporting processes. I found that the update had in fact not been done for well over a year. This is a common issue – standing data can quickly get out of date unless it is regularly updated. But because it is standing data and not transactional data, it can lose some visibility. I introduced a simple tick checklist to show when it had last been updated, making the data that was used in the subsequent reporting processes much more reliable.
2. Map the controls
All parts of a process should be controlled, in one way or another, to make sure the process is being operated correctly. If one part of a process is lacking control, it could destroy the validity of the rest of the process. The integrity of the whole process is only as good as the sum of its parts.
And a picture can paint a thousand words. So, I find it incredibly helpful first off to quickly sketch the process. Then I can overlay the controls that are being operated, and easily see if any parts of the process are uncontrolled.
Here is an example of what I mean. I was overseeing a process to take commission payments data through to reporting. By a quick mapping, I was able to clearly see that one part of the process was exposed as uncontrolled:
From this quick map, I could see that controls were in place (the blue boxes) for the start of the process. They ensured the correct files were 1) extracted from the source commissions and ledger systems, and 2) loaded into the combined transactions spreadsheet. The next part of the process was to manually cleanse that data. Taking the ledger posting as correct, the commissions transactions were manually amended if different. I found that this part of the process was totally uncontrolled. This, in effect, compromised controls over subsequent parts of the process – loading the cleansed data into the FX reporting system and then extracting the month end reports and BI. There could be no assurance that the end reported information was correct because all parts of the process to produce that information were not properly controlled.
The map enabled me to concentrate on that part of the overall process that was uncontrolled. I introduced an exception report of cleansed data – original vs. amended values – to highlight what had been amended.
3. Sense check Expected vs. Actuals
Another quick action is to insert sense-checks into a process or report. Sense checking is seeing whether data looks generally ok or not. It can be applied to the inputs to the process or to the reported outputs from the process. Is the data what is expected? Is it within expected ranges?
- Values – set a high/low limit check on values – perhaps the total for a report, or for particular cost centres. The value between one month and the next should be fairly consistent. Putting in a quick check whether the current value is consistent with the historical range will pick up on any wildly wrong data.
- Dates – set a check that all transactions occurred within the last month, for example. Or that the source file being imported was generated on the correct day – i.e. the prior month’s file has not been imported in error.
- Volumes – check that the number of lines of data is consistent with what is expected. Or that the file size of any source file is ok. Any wide variations in the volume of data being processed may suggest a problem.
4. Control totals
Another quick, but essential, check to have in place is whether the data output is compatible with the data input. Has all the data been processed correctly, or has some been missed, or duplicated? This can be checked by creating control totals.
For example, the values of the data input can be totalled, and this total value then compared to the total of the information reported. They should, apart from known exclusions, be the same.
Any differences between the totals input and output should then be analysed.
There are quick wins to be had in automating at least some of the process. Data and files can be linked to, rather than input manually, for example. As well as speeding up the process itself, this also adds an element of control because manual input can always lead to errors. An automatic link to data can be established, with a sense check control to see that the linked data is valid perhaps.
So those are my five go-to quick wins! They are what I look to implement straight away from day 1 of dealing with a process. None of them are that difficult, but they require standing back from the process to see where these are missing from and where they can be best placed.
I hope you find this useful. If you have any comments or need any help with improving your processes then do get it touch.