Harnessing the Power of Process Intelligence

Process Intelligence – Defined

Business process intelligence can be defined as analyzing a set of data related to business processes or operational workflows to identify inefficiencies and threats and enhance effectiveness. Process intelligence is the next step in process automation as it is a powerful platform that can be leveraged to identify, analyze, and manage critical business processes.   

How Process Intelligence Works?

In general, process intelligence uses process mining and task mining techniques to provide intelligence metrics. These metrics can be used to gain deeper insights into your business processes and let you analyze with a deep numerical approach irrespective of the complexity of the processes and the data sources. 

In addition process intelligence extracts and interprets data from process definition documents (PDDs). If you have timestamps and other elements they will be precisely extracted and analyzed with the relevant events. It interprets the timestamps and is visually modeled to identify inconsistencies and deviations from the standard flow. This helps in coming up with improvement plans and to enhance overall business performance. 

Benefits of Business Intelligence Process

Process intelligence lets you have a proper plan for developing an automation strategy. It helps realize the value of your business and helps identify the threats then and there. 

Here are some of the benefits that business intelligence provides:

• You can have focused insights when it comes to using automation. You can quickly identify the best outcomes and identify delays. You can enforce seamless unification in your workforce.
•  With the business intelligence process in place, you don’t have to worry about missing opportunities. It enhances your visibility and helps find the optimal path leading to increased ROI. It also helps in formulating PDDs which is important for gathering intel, visualizing imperfections in your workflows, and managing highly variable processes. You can use data most optimally and establish a system. 
• You can save time in identifying areas of threats and inefficiencies which helps you focus on prioritizing automation. The knowledge that you gain from the data helps you scale your automation better and accelerate business process automation at every step. 
• End-to-end process automation is possible with process intelligence tools. Using these tools you can empower your automation, tweak your processes, and optimize operations. Cflow is a process automation tool that lets you monitor your processes, ensure compliance, and enhance efficiency. 
• You can automate your compliance processes which are defined by data-driven tasks that align with your business goals. With this, you can set up standard rules for maintaining compliance and ensure consistency. 
• If you have RPA and IA you can have peak performance when you use process intelligence together with AI. Combining all these technologies streamlines your automated processes and ensures data-driven decisions are made throughout your organization. 

Steps in the Business Intelligence Process 

The process intelligence involves the following six stages:

1. Collecting Data

This process involves collecting data from different sources. It can be external and internal. External sources include industry analytics, market data, data providers, etc. Internal sources include CRM, Google Analytics, CRM, etc. Leveraging Google Analytics integration with Salesforce or another CRM ensures seamless data flow, helping set up your business objectives and identify which data you need to achieve your goals. Moreover, data collection enables you to collect and store past and current data helping you with improved decision making. 

2. Preparing Data

Once you have collected the required data you must prepare for analysis. This stage involves data cleaning – here you will look for duplicate data, errors, outliers, and inconsistencies. Unstructured data that you identify will have to be organized and transformed before analysis. You need to ensure that the prepared data is validated and of the required quality and consistency for analysis. 

3. Storing Data

The cleaned data is now obtained and stored in a centralized location known as a data warehouse. This data warehouse remains confidential and is secured using sophisticated data encryption techniques. This is done to ensure data safety and integrity. Access is given only to authorized people who are involved in the data analysis process. 

4. Analyzing Data

Now that you have clean data, it’s time to analyze it. The stored data is now analyzed to identify trends, patterns, and other insights. Here you will use data analytics techniques, quantitative approaches, and qualitative analysis to turn the raw data into valuable actionable information. You will be the detective here, gathering evidence by looking for clues and piecing the store together. 

5. Visualizing Data

Not everyone will understand technical data analysis. So you need to present your findings in a way everyone can infer visually. You can present the findings using charts, dashboards, graphs, and other readable visualizations. This visualization should interact and help in gaining insights into a broader audience and stakeholders to make informed decisions. 

6. Data-Driven Decision Making

Finally, you will collaborate with relevant stakeholders and team members to make insight-driven decisions. You will interact and come up with the best course of action for achieving your business goals. For instance, you can conduct a roundtable discussion with the stakeholders to help contribute their thoughts and experience to make collaborative decisions. 

Implementing Business Intelligence Process

Now that you are familiar with the different steps in business process intelligence, let’s see how to implement it effectively. 

• Getting members familiar with business process intelligence

Your team will comprise stakeholders from both technical and non-technical backgrounds. Therefore it is important to explain what process intelligences in layman’s terms. Mutual understanding between employees is essential here as people from different departments work together in data processing and ensure that they don’t confuse predictive analytics. You need to make key people understand the concept of the business intelligence process and set standards to control the data flow. 

• Objectives and KPIs

After explaining the concepts of business intelligence it’s time to set up objectives and KPIs. setting up objectives is essential for leveling up your automation:

• The type of sources used – external sources, ERP, CRM, website analytics, etc.
•  Type of data that needs to be sourced – reports, website traffic, sales, etc. 
• Data access permissions – market analysts, sales team, development team, top management, etc. 
• Report generation and presentation – spreadsheets, interactive dashboards, ad hoc reports, etc. 

In addition, you need to set up KPIs to measure progress. These help in monitoring progress and evaluating performance. Possible KPIs can be financial indicators and performance indicators such as revenue, profit margin, client retention rate, customer experience, customer satisfaction, etc. By the end of this stage, you will be able to figure out the requirements and capabilities. 

• Choosing automation tools

Process intelligence tools should have the following features. 

• Data organization – allowing data to have its hierarchy to build and organize. For instance, if you have data consisting of years, months, and days it can have its hierarchy and with a simple click, your data can be drilled down to reveal the trends by month in a specific year. 

• Drag and drop – this is a must-have feature. The tool should have a user-friendly interface where the user can simply drag and drop fields into the form, import data, analyze them, and instantly get a graphical representation. 

• Data augmentation – this is another important feature where the process intelligence tool will let you organize the data based on certain calculations such as sum, average, count, maximum, minimum, etc. You can effortlessly organize the data to your convenience to get deeper insights into trends and customer experience. 

• Data Analytics – the tool that you choose should be capable of performing advanced analytics. It should easily analyze complex data and facilitate data predictions to make potential outcomes. For instance, you can do a what-if analysis to see how your business will perform in the future and predict possible outcomes. Using this result you can get an objective view of your business performance and see the risks and rewards involved which lets you make informed decisions. Modern business intelligence tools like Cflow come with dynamic functionality that lets you perform advanced analytics based on the scenario. 

• Reporting – the business intelligence tool should be intuitive enough to let users create and distribute reports without much assistance from their IT teams. Cflow’s process intelligence lets you automate report delivery at scheduled intervals and also comes with built-in reminders that can be sent to specific people at needed times. Moreover, Cflow offers interactive reporting tools that let you interact with different reporting formats that can be customized based on your business needs. 

• Security – this is a highly important feature that should never be compromised.  Your data will contain sensitive information that cannot be shared or accessed easily. Therefore, the business intelligence tool must have several layers of data encryption and data restrictions on particular data sets. The tool should allow you to personalize the features and provide user-specific data permissions that change based on the user and the location.  

• Form a team

You’ve got your tool and now it’s time to gather people and form a business process intelligence team. You need to select potential people from different departments and work together to establish a business intelligence strategy. 

The first category of people would be domain experts. These people will be responsible for contributing and interpreting domain knowledge as well as providing other teams with data sources. For instance, you can have a marketing specialist here who can provide you with details on how your website performs and a sales specialist will tell you potential prospects that would generate revenue. 

The second category of people would be PI-specific roles. These members would be selected based on their unique talent that would lead to development, architecture, technical, and other aspects of the business intelligence process in your organization. The team should have a head, engineer, and data analyst. 

• The head of the PI team would be responsible for imparting theoretical, practical, and technical knowledge in implementing business intelligence strategies. They work towards successful implementation throughout your organization. 
• The engineer would be specializing in building and implementing business intelligence systems. They will be responsible for data configuration, and software development and be proficient in data integration approaches.  
• Finally, the data analyst will be proficient in doing data validation, processing, and data visualization techniques. 

• Documentation

It is strongly recommended to document your business process intelligence strategies. The BI strategy will include several components that differ with businesses – company size, type of business, competitors, business model, revenue model, shareholders, etc. 

The documentation should contain detailed information on data source channels, performance metrics, KPIs, data flow, and any other relevant information that fits into your company’s reporting standards. The reporting can either be done traditionally or you can make it self-service. The traditional approach has more control and security over data flow as it goes through different stages of approval. However, self-service reporting is more of a laid-back approach where the reporting gets automated and doesn’t require different stages of approval. Reporting done traditionally is far less secure compared to self-service ones as the latter reports are automated and stored in the data warehouse. You need to choose the best approach based on your company’s needs.

• Architecture and Implementation

Architecture should include both the organizational aspects and the technological infrastructure of the business process intelligence. The technological aspects include data engineering which comprises these elements:

• Data integration tools (ETL – Extract, Transform and Load)
• Data sources
• Data warehouse
• Analytical processing cubes
• Data marts
• Reporting tools

When you implement these phases it will require immense technical expertise and a lot of time from your IT team. But all these structural elements will be developed, customized, and implemented when you choose a vendor like Cflow from the market that can do all the data structuring for you completely based on your organizational needs. 

• Training

After you have implemented BI it’s time to conduct training sessions for your employees. These sessions should cover all the technical aspects of your tool and should be interactive.  

Hyperautomation – The Next Level Process Automation

Before that let’s see briefly what intelligent automation is and how it differs from process intelligence. 

Intelligent process automation (IPA) refers to the process of integrating process mining, robotics and other technologies such as artificial intelligence (AI), machine learning (ML), and business process management (BPM) to transform and efficiently manage business operations.  This is sometimes referred to as hyper automation helps think, learn, and transform business process automation.

Need for hyper-automation 

The strength behind intelligent automation is its combination of AI and other technologies allowing you to make consistent data-driven decision-making.  It improves your existing process without compromising quality and doesn’t put a strain on your workplace. 

Among the many benefits,  IPA lets you establish modern, resilient, and flexible operating models for facilitating end-to-end business processes. Combining hyper-automation with human experience lets you have the expected innovation in creating business value. 

However, successful implementation of IPA requires extensive teamwork between business function teams and your IT team. Their collaboration will result in scalable and sustainable changes to the process framework. Your employees must be a part of this transformation. 

Intelligent automation simplifies processes and enhances operational efficiency. For instance, an automotive manufacturer can use hyper-automation to increase production speed and reduce human errors. An insurance company can benefit from hyperautomation where they can simply calculate payments, make predictions, and manage compliance. A life science company can use intelligent automation to manage their repetitive processes and reduce costs in gaining resources. 

Major components of intelligent process automation

Three major components make up hyper-automation – (i) AI (ii) BPM and (iii) RPA. integrating these three components enables you to get a transformative solution that can optimize your workflows and enhance customer experience.

1. The first and most critical component of hyper-automation is AI – artificial intelligence. Combining AI with ML and other complex algorithms you can create a knowledge base that can make predictions based on data which becomes the decision engine.
2. The second component is the BPM – business process management. Otherwise known as business process automation or workflow automation is the component that automates your workflows and provides agility and consistency in managing your business processes. BPM also helps enhance engagement and experience.
3. The third and final component is the RPA – robotic process automation. It uses bots or software robots to complete tasks such as data extraction, support, form filling, etc. These bots leverage the benefits of AI and RPA to handle more complex tasks. 

How cflow’s Business Process Intelligence Works

Cflow is a recognized leader in the business process automation market and holds its competitive edge consistently. Cflow is a cloud-based business process intelligence automation solution that has pioneered the drag-and-drop interface and no-code automation functionality. It is highly scalable for both small and large businesses regardless of the type of industry. It offers complete front-end and back-end data analysis, advanced analytics, designer dashboards, smart integration, ad-hoc reporting, etc. 

There is so much more that Cflow can offer for your business. Visit our website to know more about Cflow’s limitless capabilities and sign up for a free demo today!