Process Intelligence
Learn how to develop complete process intelligence, with full visibility into all service and communications workflows.
What is Process Intelligence?
Process intelligence, also known as business process intelligence, is the insight gained from data that has been extracted from a business process or operational workflow.
Process intelligence is a critical component of process improvement, playing an important role in helping define processes and identify areas of inefficiency for improvement programmes.
Process Definition
A process is a progression of actions, steps or events that usually proceed linearly from a defined starting point to an end point or outcome. Processes exist to create a general, consistent flow of events that lead to an intended result in the most efficient or optimal way. When viewed alone, a single process step may be of little value. But when viewed as part of the larger process, individual stages start to reveal their real utility.
Good process intelligence depends on both perspectives. You must be able to drill down into individual stages, but you must also have visibility across the entire process as a whole - tying all stages together.
Processes will usually emerge organically as people try to work out the best way to achieve a desired outcome. However, they can also be implemented top-down - planned in advance before they are deployed to a real-world context. Regardless of their type, processes are constantly changing. They adapt to external forces, or are being mined for process intelligence for the purposes of process improvement.
Business Process Definition
Business is run on processes. Depending on the size and complexity of an enterprise, it can take hundreds or even thousands of processes for a business to meet its objectives.
The majority of business processes are small in scale and tactical in nature. They are processed manually by employees or automatically by automation bots.
However, certain processes are absolutely critical for the successful operation of an organisation. Whole departments, or even the entire enterprise, are impacted and depend on these important processes. Changes focused on these mission-critical processes usually have the biggest impacts on organisational efficiency. This makes them the core focus of many process intelligence and process improvement programmes.
Some of the most common core business processes are:
- Accounts payable (AP)
- Accounts receivable (AR)
- Customer service
- Inventory management
- Order-to-cash (O2C)
- Order management
- Procurement
- Purchase-to-pay (P2P)
Every business will define its own processes differently. Culture, resources and even other processes will constantly shape a business process, meaning they are never static and constantly changing. As elements change and new ones are introduced, problems and inefficiencies can often emerge. This makes real-time process intelligence critical - to identify and stop these inefficiencies before they can snowball into disruptive crises for the business.
What’s the difference between Structured Processes and Unstructured Processes?
Owing to their diversity, business processes can be infinitely divided and categorised by their owners. Heads of departments will usually focus on the largest, most business-critical processes they are responsible for, while managers concern themselves with the smaller, tactical processes employees are engaged in.
However, when it comes to process intelligence, there are two different types of processes that are most likely to help or impede process improvement efforts.
Structured processes
It’s inevitable that many business processes will have to interact with corporate IT systems to reach completion. These interactions produce event log data which can easily be read and analysed by machines and systems. The presence of such data makes the related processes much easier to understand and track. It also opens the door to process automation. Clean structured data can be passed downstream to automation tools, such as robotic process automation (RPA), for straight-through processing.
As businesses strive for cost savings and greater efficiency, more and more structured processes are being automated from end to end, freeing employees to focus on more complex tasks. However, there are only so many structured processes in a business, and transformation agents are beginning to run out of road. Interest is, therefore, growing around the second major process type:
Unstructured processes
The vast majority of processes in a business can be described as ‘unstructured’. Unstructured processes do not directly interface with corporate IT systems and, therefore, do not produce data for analysis or automation. Indeed, an estimated 80-90% of all data generated in a business will be in an unstructured format.
It’s worth remembering that every business process that depends on human action will become unstructured at some point. This happens when an employee goes outside of core systems in order to do their work.
Some of the most widespread unstructured processes in a business include:
- Sending an email to a client
- Messaging a colleague on an instant messaging app
- Triaging a support ticket to the most appropriate team
- Making a phone call to a customer
In none of these examples is an actionable data log created, even though each uses some form of digital communication to complete. This is because any process based in communication will be expressed entirely in unstructured data. Unstructured data is data that can’t easily be understood by machines in its raw format - it can include formats like videos, but in a business context will be anything that contains a large amount of natural conversational language - such as email conversation and phone calls.
The problem is that unstructured processes are important. Some of the most widespread, valuable but least efficient processes in a business will be partly or almost entirely unstructured - mediated through human conversation and interaction. Key service functions like Shared Services and Customer Service are based in unstructured, communications-based processes. It’s estimated that the time employees spend processing emails costs businesses between $5,000 to £10,000 each year per every single employee.
Communications affects almost every process in the enterprise. Yet unless the enterprise has the capability to process unstructured data, such processes will remain beyond the scope of process intelligence and improvement.
Why is Process Intelligence Important?
Businesses have woken up to the importance of processes to their overall success. Everything from service to output, customer experience and productivity depend on the efficiency and successful running of a businesses processes. As a result, process efficiency has become synonymous with competitive advantage as the leading businesses compete to maximise profits while minimising costs.
However, you can’t improve a process unless you first understand it. Furthermore, efficiency is not always the be-all and end-all of process improvement. In many processes, customer outcomes are far more important than bare efficiency - though the two often overlap. For example, embedding chatbots at the first level of inbound customer support requests may make the process more ‘efficient’, but they may also degrade the customer experience - thus betraying one of the most important aspects of customer service.
To really understand a process, how efficient and successful it is at meeting its goals, you need more than simple metrics like handling times and cost. You need process intelligence. This means having detailed, granular and real-time insights into all your mission critical processes, both structured and unstructured. You need to know how efficient they are, where there are opportunities for improvement, but also key intent data on the causes of inefficiency and the drivers of contact and workflow.
Process intelligence separates market leaders from the rest of their industries. Insight is power, especially when it comes to process improvement and achieving competitive efficiency.
What are the Advantages of Process Intelligence?
Process intelligence is a crucial enabler of process improvement, revealing automation opportunities, driving cost out and helping you maintain SLAs and compliance.
Process intelligence has many benefits for the enterprise:
Increased process improvement ROI
Stakeholders gain unprecedented visibility into the causes of failure and inefficiency within their function or organisation. They have the insight to make the most valuable change opportunities, multiplying the success of their process improvement initiatives.
Improved total experience
Real-time visibility over all processes, structured and unstructured enables you to intervene rapidly to resolve emerging issues and challenges. Stop problems before they do damage to your business and services.
Better compliance
Process intelligence helps you to maintain compliant practices and processes across your business. Increased visibility and faster reporting makes it easier to fulfil regulatory requirements and adhere to customer SLAs.
Enhanced business intelligence
Understand and accurately model how your business operates by gaining complete insight into all business processes.
Improved customer intelligence
Understand your customers better than ever by getting accurate, real-time insight into their wants, needs and intents. Adapt your services to give them the best possible customer experience.
How do I improve Process Intelligence?
Process intelligence is the first and most important step on the road to process improvement. However, to ensure the highest chances of success, there are numerous requirements you should aim to satisfy.
To improve process intelligence, you need a comprehensive understanding of all processes within your organisation, structured or unstructured. This is achieved through a multistage process called process mapping:
- First, identify the process and give it a name. Your starting point should be core business processes.
- Define the process’s scope. Detail whatever events are included in the process stream.
- Establish the process’s boundaries. Ensure you understand where the process begins and ends, as well as what triggers the process to begin.
- Identify the process inputs. Establish what resources are necessary to complete the process.
- Enhance your understanding of the different process steps by gathering the insight of the employees involved. Many businesses make the mistake of considering this the most important and efficient way of gathering data on processes - but it is only a way to enrich existing understanding.
- Create a process flow by organising the steps in a linear sequence.
- Establish who in the organisation is responsible for each process step.
- Uncover and outline any exceptions to the normal process flow.
- Add control points and measurements to the process.
Given the complexity of businesses and their processes, you will likely need a range of tools and intelligent automation solutions to extract all the data you need. Shortcuts and half measures at this stage will compromise any attempts at long-term process improvement. You cannot expect widespread, impactful changes with only partial process visibility and insight.
What are the Best Process Intelligence Tools?
Different process types will require different tools and solutions. The most effective process intelligence tools focus on data extraction, helping you build a detailed, data-driven understanding of your business processes. Sparing stakeholder interviews should be supplemented with the following:
Communications Mining
Communications Mining is an important process intelligence tool that’s needed for extracting data from unstructured processes. Communications Mining extracts valuable information from communications and service workflows - including shared email boxes - to enhance the business’s understanding of the process. This includes intent data (the drivers of work and the process) as well as sentiment and other important insights.
Communications Mining is a foundational tool for process intelligence. It presents the only way to quickly and effectively extract structured, actionable data from unstructured processes. It achieves this through a combination of machine learning and natural language processing, interpreting business communications in real time and transforming it into structured data, at speed and scale. This removes the need to have employees waste valuable time and effort attempting to extract this data through manual logging and analysis.
The coverage it provides makes Communications Mining an ideal complementary tool for other process intelligence tools. For example, Communications Mining surfaces potential areas of process improvement, which can then be analysed and assessed further with Process Mining.
Find out more about how Communications Mining and Process Mining work together.
Process Mining
Process Mining is a class of tools that help users discover, monitor and improve processes within a business. Process Mining works by constructing and visualising detailed process maps using data that’s extracted from the corporate IT system. Process Mining is useful in that it presents a picture of business processes that is informed solely by data. This is in contrast to manual process mapping exercises which are informed mainly by subjective stakeholder opinions and viewpoints.
However, Process Mining is somewhat limited in that, while it can describe a process and highlight points of inefficiency, it cannot show you the root causes. To understand the ‘why’ of process inefficiency (something critical for complete process intelligence), you need to leverage Communications Mining.
Task Mining
Task Mining is a process intelligence tool used for collecting data on the individual manual activities of staff. Task Mining captures user interaction data - such as the frequency of mouse clicks on a desktop - to help business leaders understand their productivity, speed and performance of their employees on a task-level.
Intelligent Document Processing
Intelligent document processing (IDP) uses a combination of AI and optical character recognition (OCR) technologies to extract structured data from unstructured and semi-structured text documents. When paired with solutions such as Communications Mining and Process Mining, IDP contributes to full coverage over all data sources that could contain actionable insights for process intelligence.
Process Intelligence and Re:infer
The Conversational Data Intelligence Platform from Re:infer, a UiPath company, creates comprehensive, real-time process intelligence that greatly augments process improvement initiatives.
By transforming unstructured communications into actionable process data at speed and scale, Re:infer enables unprecedented process analysis and automation. For the first time, businesses can extend process intelligence and improvement into even the most complex manual processes based on human language and conversation.
Re:infer Communications Mining monitors business communications in real time. It constantly surfaces process inefficiencies and opportunities for deeper analysis and automation. Re:infer also offers customisable reports and real-time alerts, flagging process issues as they happen and giving users the time to rapidly resolve them.
Re:infer Conversational Data Intelligence provides full, no-code natural language processing capabilities that start delivering value after a short training period. No technical experience is needed to train or use Re:infer models, making it an ideal solution for the enterprise. Re:infer has worked with many companies to extract the value from conversational data, enhance scalability and improve the customer experience.
