Collectively, we produce over 2.5 exabytes of data every day, a figure that includes all of the information produced by businesses as well. It seems like this treasure trove of data would be invaluable to a business — think of all the patterns, predictions, and actionable wisdoms that lie locked away in your data!
Trouble is, those insights are truly locked away, and data tend to be scattered about and siloed. If you want to capitalize on the hidden troves of data your business generates every day, you need to turn to business process analysis.
Simply put, business process analysis is the assessment of the efficacy and efficiency of the many, many processes that make up your business. Ideally, your business process analysis will unearth opportunities for improvement, enabling your organization to increase productivity, control costs, become more profitable and achieve other business goals.
A business process evaluation could assist a telecom in predicting peak usage hours to determine when to activate more network bandwidth and server processing, for instance. Or it could improve the invoicing process of an enterprise company to save time and cost.
IT organizations could analyze their ticket system to identify systemic patterns of issues or root cause application failures, or healthcare organizations could streamline their claims adjudication process. Virtually any business or job role, from IT manager to financial operations manager, can benefit from a thorough process analysis to become more efficient, save on costs, and raise its bottom line.
Broadly, business process analysis follows four basic steps.
Most businesses have a general idea of what processes could be improved, how to analyze their problem and how to make a plan to fix that problem. Accessing the data that this whole process runs on, however, is no easy task — not to mention organizing your processes based off on that data.
In a typical organization, so much of the necessary data is siloed. Processes are spread across multiple managers and teams, so details get lost along the way. Information is stored across departments, isolated within individual roles and locked away in different formats like spreadsheets, text documents or even video.
With these isolated pools of data and different data formats, it can be hard to identify patterns. Without the ability to compare and contrast or view a problem through a different lens, the business suffers.
You have a variety of ways to comb through your business's data to unlock the information you need. You could always take the old-fashioned and laborious route — that is, tasking a team with looking through every document, spreadsheet, recording and manual that may be related to your process.
This, however, clearly isn’t the optimal approach. If you don't have an expert on hand, you'll need to bring on individuals with the necessary data science skills to collect and analyze your data. However, even with the right talent, this is a time-consuming task that isn't the best use of your team's time. What's more, your team is made up of people — fallible people who sometimes make mistakes. Since a business process analysis is only as good as the data that the analysis is conducted upon, errors in data collection can cause you to reach the wrong conclusions about where to go next.
Instead, you'll want to use an automated solution. Broadly, there are two approaches to process automation: robotic process automation and intelligent process automation.
Some may be more familiar with robotic process automation, or RPA, which mimics mouse movements and keyboard strokes. Depending on the nature of your business process analysis, an RPA approach could be sufficient.
If your data collection efforts just require you to, say, click in one field and copy-paste the data to another thousands of times, RPA is the way to go. RPA can easily replicate tedious work relying on structured data — that is, clearly defined and easily searched data.
RPA, however, doesn’t do so well when processing unstructured data.
Ninety percent of the data that we produce are unstructured; they're locked away in images, video, recordings and other messy formats that machines don’t interpret too well. But just because these data are unstructured and unfriendly to machines, doesn’t mean that extracting them is a job for humans.
Unstructured data extraction and processing are still very repetitive and time-consuming tasks. It's easy for humans to make errors in carrying out, which is why a business process analysis should rely on intelligent process automation, or IPA.
IPA is quite similar to RPA except that it incorporates artificial intelligence. This makes IPA better at understanding context and ingesting non-standard data formats that don't always sit well with less intelligent techniques. IPA uses advanced processes like NLP (natural language processing) and OCR (optical character recognition), which enable the program to understand words on scanned documents and other formats just as well as a human.
If you're planning on running a business process analysis, you'll want to evaluate your data sources. Are there a lot of images, PDFs, interpersonal communications and other unstructured formats? If so, an IPA solution is where you'll want to go to first.
Once you’ve unlocked your data from the many silos spread out across your organization, that information will be available for you to analyze and interpret. Good data is fundamental to business process analysis, so accurately getting as much relevant data as possible is key to identifying opportunities for growth and improvement in your business.