The significance of a company’s data strategy in connection with its decisions regarding process mining should not be underestimated.
Data strategy entails the organized plan for handling and utilizing data within a company, whereas process mining involves using data to uncover, observe, and enhance business processes.
These two ideas are frequently treated as distinct entities, and often, there are barriers between the teams responsible for data and those focusing on processes in larger organizations. Yet, when these teams collaborate effectively, process mining and data strategy can combine to create a potent tool for achieving business success.
This article delves into the correlation between these two aspects and explains why it’s essential to make decisions about them jointly to maximize their advantages.
The role of data in modern business strategy
In the past, data used to be a byproduct of business activities, and its significance extended only to the initial task or process. While certain subsequent tasks might have required the data, its value wasn’t highly emphasized.
However, in today’s landscape, data has transformed into a pivotal element of numerous new business ventures. This transformation is due to advanced data collection, reporting, analytics capabilities, and the sheer volume of data generated. It’s now customary for application data to be shared across multiple systems for various purposes.
Despite this change, many companies still struggle to achieve their objectives related to capturing, sharing, managing, and analyzing their corporate data resources.
When an organization establishes a clear and well-defined data strategy, it gains the ability to utilize process mining to harness its data for enhancing its processes.
How is process mining related to a company’s data strategy?
Data serves as the foundation for process mining; without data, the practice of process mining would be impossible.
However, what often gets overlooked is the connection between the decision to invest in process mining and the broader data strategy.
Data is like the essential ingredient or raw material for process mining. This underlines the importance of considering that even if a company isn’t fully prepared for process mining at present, the data strategy should be flexible enough to accommodate it in the future.
Let’s illustrate this with an example.
Imagine a company where the top management and data team have decided to implement Data Warehouse X and migrate all ERP data within the next 2-3 years.
Given that the choice of data storage, like a cloud or warehouse, usually has long-term implications, a logical approach to the data strategy is to factor in which tools or providers could seamlessly integrate with that data storage solution in the future.
In modern practices, there’s no need for complicated data integration, as applications can directly operate within the warehouse resources without needing to relocate the data elsewhere.
For instance, if the company plans to explore process mining once the ERP data is successfully transferred to the new data cloud, it becomes crucial to conduct research and possibly make preliminary decisions regarding which vendor aligns well with their chosen data warehouse solution.
A Real-life Example: QPR ProcessAnalyzer and Snowflake
Snowflake Data Cloud’s distinctive architectural design provides a platform for data storage, processing, and analytics that outpaces traditional data warehouses in terms of speed, user-friendliness, and adaptability.
QPR ProcessAnalyzer can function on any data lake by utilizing its in-memory engine. However, it stands apart as the sole process mining software that operates natively within the Snowflake Data Cloud. This positioning allows it to leverage the cloud’s scalability and unified data policy.
By employing QPR ProcessAnalyzer, you tap into Snowflake’s virtually limitless scaling capacity, enabling you to swiftly uncover process inefficiencies from immense datasets with incredible ease.
“We connected to Snowflake in 5 minutes and saw results the same day. We’ve never seen anything like it.”