By James Berracoles, Solutions Engineering Manager, iGrafx
No matter what industry or vertical you’re in, a few principles are true across the board.
For one thing, your business must have a solid value proposition that differentiates it from competitors. For another, you should understand, and prioritize, your customer or client’s needs, while making decisions that improve both customer relationships and the bottom line.
Honoring these principles might mean finding ways to be more efficient, offering better services or products, or streamlining existing offerings and processes to unlock new value.
Whatever the goal, the key to making real improvements is data – specifically accurate information about how your business is currently operating. It also involves identifying areas where you can do better.
Often, however, decisions are made based on how business leadership thinks things are running rather than the reality. But there’s no way to know that if the actual business processes aren’t quantified, measured, and examined in-depth. This leads to a situation where any changes made don’t really address business needs and the company comes up short.
To solve that shortfall, businesses today are increasingly turning to process mining for answers.
Process mining in a nutshell
Using process mining, businesses can tap into the data available from the software used in day-to-day operations. Looking into the logs of CRM (Customer Relationship Management) or ERP (Enterprise Resource Planning) software, for example, can help businesses understand how their processes are unfolding.
How long does it typically take for a transaction to be processed? Are there any areas where work is being repeated, or are errors causing costly delays? Are all the necessary steps in place to ensure regulatory compliance?
Process mining provides answers to these vital questions. It gives business leaders a tangible basis for making meaningful change.
Delving into the data
Consider the example of a company investigating the buyer’s journey. Using process mining, this business analyzes the steps in that journey across multiple systems and discovers a large delay between initial customer inquiry and contact with a sales rep.
As a result, a larger than expected proportion of potential sales are slipping through the cracks. Customers go elsewhere to find what they need.
The business also discovers this is happening primarily in one specific office. A second office in a different region has much faster turnaround times.
Given this information, it becomes possible to investigate both what’s gone wrong at the first office and what’s being done right at the other.
Actionable insights
Using the information gained from mining the process and subsequent investigations, the company identifies the optimal version of its sales process. This best practice process can then be standardized across all offices.
The business can also provide updated protocols and training for employees, bringing the lagging office up to the same standard as the other. Customer experience is improved and sales revenue boosted – on the back of the insights gained from mining the process.
Furthermore, companies can use process mining to ensure their compliance with regulatory standards. They can, for example, identify necessary steps that must precede the next stage of a process.
They can then use that information to further optimize or even automate compliance processes, reducing the risk of financial penalties. This helps protect them from reputational damage that could arise if sensitive data were mismanaged.
An analytical edge
As the above examples show, the information gained from process mining can be very valuable. To realize that value, however, businesses must ensure that mined information is not only accurate and up to date but also delivered when actually useful.
For the accuracy piece, you need to ensure the tool you’re using properly differentiates when steps occur in your process. For example, if two steps occur simultaneously, the tool must be able to discriminate that and record actual process times rather than counting these steps separately.
This principle, called concurrency, is vital to ensuring the accuracy of mined data when processes can follow multiple pathways.
For the second piece, the tool you’re using should be able to analyze how processes are executed over time. This way, the outcome of suboptimal processes can be predicted. In other words, instead of telling you a process has failed after it’s happened, a good tool should alert you to this possibility ahead of time. The process can then be adapted or changed before the problem ever occurs.
These two features, concurrency and predictive analytics, are key components of iGrafx’s process mining module. It’s only by adding a further component to the mix, however, that true process optimization is unlocked.
Integrating process design
To maximize the value of mining, it must be combined with the ongoing monitoring and optimization capabilities offered by process design.
Where mining gives you initial information on what’s happening in your processes, the design piece adds the capability to tweak and refine processes in accordance with business needs and goals.
This isn’t to say that the process mining piece is a “one-and-done” component. It’s more of a conversation between the two. After design, you use mining to check that your modified processes are performing as expected. Then you tweak, adjust, or redesign as needed.
Business as usual, but better
The result is a powerful tool for streamlining and improving processes on an ongoing basis – both in real-time and proactively. Importantly, it is a tool that does all the heavy lifting for you.
This leaves you to get on with the real work of your business: Building the value proposition and customer relationships that will carry you forward for years to come.
Interested in learning more about iGrafx’s process mining and optimization solutions? See our Process Mining product page here or contact us for a free demo.