Every sector has repetitive, manual processes that can be automated to improve productivity and the real estate industry is no different. There are several data processing tasks in real estate and property management processes such as accounting, inventory, procurement, document management, and so on. 

All of these processes are time-consuming and reduce the productivity of the employees and the business. And by automating them, real estate companies can focus on more important tasks. An automation technology that’s increasingly popular in the industry is Robotic Process Automation (RPA).  For those not familiar with this technology, we’ll like to point out that there are no actual robots involved. Instead, RPA is a piece of software, an advanced one for that matter, that can simplify a lot of processes in the real estate industry and significantly boost productivity. More information and applications of RPA in real estate to lead your business and reduce costs are described thoroughly below.

Let’s begin with a definition of RPA.

What is Robotic Process Automation? 

RPA is all about instructing a computer program to carry out mundane and repetitive tasks. These repetitive tasks tend to be tedious and time-consuming when carried out by humans which results in lower productivity of employees and ultimately that of the business.  Using RPA, however, increases productivity as the software can perform high volumes of tasks with high speed and accuracy.  

RPA is especially useful for processes and tasks that don’t require human intervention. Take for instance that you regularly input tax numbers into a spreadsheet which you use to generate reports with specific search criteria, you can use RPA to automate the process.  “This means the bot will fill in the tax numbers for the run, run the search criteria, and generate the report just like you would do. You just need to teach the software workflow with several steps and applications,” explains Ruban Selvanayagam of Birmingham auction house Property Solvers.

How is RPA Relevant to The Real Estate Industry? 

Real estate agents and realtors are already using the automation power of RPA for data entry, data migration, data extraction, data validation, and data update.  

This has resulted in reduced errors and workload of employees and the entire operation of businesses is faster and more efficient.  

Real estate isn’t the only industry benefiting from the RPA. Other sectors like banking, insurance, telecom industries, financial services, supply chain, and mortgage lenders have already adopted the technology.  

Real estate businesses should also strive to adopt RPA and enjoy its benefits as doing so is cost-effective. RPA can also be embedded within the existing IT structure, so the adoption should be quite straightforward for most businesses.  

Applications of RPA in Real Estate 

There are several processes in the real estate industry that RPA can automate. Here are some of the applications of RPA in real estate: 

1. Tenant Onboarding 

Tenant onboarding is one of the most tedious and crucial processes for real estate businesses, especially those that manage a lot of properties. The experience of a client during the onboarding process can make or break a business as most real estate transactions are referrals. A customer with a bad experience is unlikely to recommend a business, right? 

From carrying out background checks to verifying income, identity, employment, references, and insurance details and providing concise information during lease signing, there’s a lot to achieve with RPA during the onboarding process. Through the power of automation, RPA can make the onboarding process and tenant management, as a whole easier.  Most of the onboarding processes can be easily automated which will make tenant processing quicker. Tenants will also have good experience which is important to running a successful real estate business.   

2. Payment Reminders 

Late payments. Two words real estate companies do not like and for good reasons. Unpaid invoices can make businesses incur huge costs due to loss of operating capital, time and energy spent chasing overdue customers (time is money, after all), paid interest on loans to cover cashflow shortfalls, and so on. However, late payment is something many real estate companies will encounter from one point to another. And chasing unpaid invoices can lead to lower productivity.  

Generally, processing invoices is a paper-intensive task that requires a lot of working hours and has a high scope for errors. RPA offers the opportunity to automate invoice processing by setting up bots to extract key information from purchase orders to create invoices. The invoices generated and processed by bots are of higher quality since the number of human errors in the data and the entire process is reduced. This frees up significant working time and allows employees to focus on more important tasks. Also, clients are billed on time and automated reminders can be sent to those that are yet to clear their invoices.  

3. Portfolio Management 

Many real estate companies invest a lot in static assets and as such, must monitor these assets to ensure they become profitable or generate revenue. This may involve selling or renting out properties. To achieve this, assets are listed on several websites. Sometimes, there may be a need to change some information or the status of the asset. For example, if a property has been rented or sold out or if the asking price has changed.  

Any of these changes will have to be effected everywhere the property is listed and this can become very tedious for those with large holdings. By using bots through the power of RPA, the process of editing property information across several platforms can be automated.  

Also, real estate businesses collate information about assets from different sources for intensive analysis and insights. Data may be collected from email applications, internal spreadsheets, investment management IT systems, and external websites. Instead of workers manually collecting information from these sources, bots can be trained to do so resulting in fewer errors, reduced workload, and improved performance of employees.   

4. NAV Calculation  

One of the best ways to calculate the value of a Real Estate Investment Trust (REIT) is to calculate the Net Asset Value (NAV). NAV is calculated by subtracting outstanding debt, the cost of planned expenses, and the cost of any fixed expenses from the total value of an asset.  

NAV calculation is tedious and monotonous at best for large companies with several assets. But by using RPA, NAV calculations can be easily done with minimal errors, and employees can focus on more important tasks like NAV validation and providing their insights on other aspects of the business.   

This improves employee morale and productivity in the real estate industry.  

5. Bank and Account Reconciliation 

Reconciliation is an important financial process in the real estate business. Bank statements need to match with the business ledger dollar for dollar, and cent for cent. If they don’t tally, then there is an issue somewhere. Reconciliation can be done weekly, bi-weekly, or monthly depending on the size of the business.  

The process, which is generally tedious, can be simplified through RPA.  RPA can extract different bank statements and put them in a single folder for reconciliation with a business ledger. And this can save the real estate business precious time.  

Benefits of RPA for Real Estate Businesses

The benefits of RPA in the real estate industry can be easily deduced from all that has been discussed above. They include: 

1. Significant savings in working hours 

The several hours previously spent on high-volume and repetitive tasks by employees are freed up when the process is automated. This results in lesser workloads and allows employees to focus on more critical aspects of the business.  

2. Increased Productivity 

Bots can run 24/7. There is no overtime and no increased cost. They do not need rest.  

3. Increased Accuracy 

Not only are repetitive and manual processes time-consuming, but they are also highly prone to errors. RPA eliminates the human errors associated with tedious and repetitive tasks thanks to the power of automation.  

4. Process Transparency 

RPA can create transparency for many real estate businesses as there’s a single track record of activities. The real estate processes become more transparent by way of providing a detailed report on how the RPA has been working. It also provides an audit trail so that you can see what, when and how much work is done. This makes it easy to account for and trace any activity thereby increasing transparency in the business.  

Challenges of RPA in Real Estate 

Despite the benefits RPA has to offer real estate businesses, there are a number of challenges to the adoption of the technology compared to other traditional real estate software available today on the market. The main challenge for leaders and forward-thinking executives is the adoption of the change. Organizations need someone to lead the adoption of innovations and RPA. 

Also, there is the problem of which process to automate with RPA. Many organizations automate the wrong process or even attempt to automate the entire process.  

Comidor Solution

Real estate companies need senior leadership committed to transforming the business with the power of RPA. These types of leaders tend to have a great appetite for improved productivity and efficiency in business processes. To avoid the pitfall of automation the wrong process, companies can consider automating one or two of the most recurring tasks and scale up from there. We’re not saying that you should automate everything from the get-go. The first step is to identify one or two tasks that are time-consuming, repetitive, and frustrating for your team. Automating these tasks will give you a quick win, and make it easier for your team to focus on more important projects. Once you’ve got automation down pat, the next step is to automate end-to-end all of your core processes. This will allow you to manage all of your day-to-day business operations, reduce costs and boost business productivity.

The best software solution powered by RPA features is the one that provides comprehensive training and support. Our platform is not just a place for automation, but also a place for knowledge and experience. We have a team of experts that are ready to help you get started and take your business to the next level through intelligent automation. Contact us today and get started with Comidor.

Businesses around the world are constantly evolving. Thanks to research and technological advancements, they can embrace different systems and technologies to improve business performance. The supply chain industry that involves the distribution of goods and services to consumers, has now adopted the use of Robotic Process Automation (RPA) to automate repetitive work. This enables human labor to perform other tasks that require critical thinking and decision-making.

RPA makes the supply chain processes more efficient. RPA addresses tangled technological elements in supply chain management. With RPA, any changes in the shipping schedules are delivered with efficiency. Therefore, no delays will pop up in the way. Whenever your business must take care of client needs or maybe implement data consolidation or automation, you can also rely on RPA.
If your organization decides to utilize RPA, it will not fail to realize how efficient its supply chain becomes. Unfortunately, a lot of supply chain companies are not convinced about the importance of using RPA in their processes, which is why we will share some benefits of RPA in supply chain management and also 5 top supply chain management RPA use cases.

Understanding RPA

RPA stands for Robotic Process Automation. Mainly, people use RPA to automate repetitive, difficult, and time-consuming tasks. For example, they use RPA to perform tasks such as data entry in a supply chain business. A worker no longer has to do manually this repetitive task.

RPA is also ideal for tasks and processes that do not require any special knowledge. It is almost the same as cognitive automation, whereby AI agents perform tasks just like a human after understanding how a human thinks. The main difference between RPA and AI is that with RPA, human skills are needed to set rules, and manage the bots. Yet, with cognitive automation, humans are replaced, or the number required is minimized since AI uses algorithms and data to understand human functions.

5 RPA Use Cases in Supply Chain Management

1. Initiating purchase orders

The purchase order process can be part of a bigger procurement project, and it is usually a tedious task for any business. It requires a lot of time and effort to manually process purchase orders. This is where RPA comes into play. RPA has the ability to automate the entire purchase order process from start to finish, save valuable time, eliminate human errors, increase productivity, and make the entire process much more efficient and cost-effective for companies.

RPA Implementation in purchase order processing includes:

• Generating automatically purchase order documents
• Submitting the order for multi-level approvals
• Automating data entry

2. Managing orders

This supply chain RPA use case concerns order processing and management. There are a lot of customers placing wholesale orders from different points, and an efficient cloud platform with RPA capabilities is the right solution for your online business. It will automatically process the orders and keep the necessary data before any shipment or invoicing. If your business is B2B, the order management process in your supply chain should be more detailed to handle the heavy traffic of orders. All in all, any supply chain company or department using RPA will be able to automate many processes without a hurdle.

3. Handling support requests and after-sale services

RPA can fully automate ticket management and after-sale services. Instead of any human intervening, RPA will efficiently perform the needed tasks. RPA technology can support the entire support department, by minimizing ticket processing errors and saving your representatives’ valuable time. This will be important to the business as it will become more competitive.

4. Supply and demand planning

Anticipating and reacting to the supply and demand process can be a daunting task especially if you just rely on human labor. To plan the reaction to the process, you will need to analyze reports and data from all corners of the business. RPA performs all these tasks without any mistakes and without wasting time.

5. Enabling data transmission

This is an essential supply chain management RPA use case. Important shipments must be transported and stored efficiently, safely, and quickly. For this to occur, data transmission must be reliable. If not, the business will incur losses because it cannot act on the correct information. RPA smooths out the functioning of analytics. This is accomplished by providing insights that will help to eliminate any clerical roadblocks such as incorrect data formatting.

What are the Implementation Steps of RPA in Supply Chain Management?

When implementing RPA applications in supply chain management, there are a few steps you have to follow:

1. Define the scope of Robotic Process Automation and its objectives

Each business has short-term and long-term goals. Incorporating RPA in your company will assist you in achieving those objectives and reaping the benefits. The most important is to determine the objectives and how they will be measured in terms of business success or failure. Let’s say your sales team receives new order for a customer. After checking the inventory stock, an RPA bot places the order to an ERP system, speeding up the whole process. Will your company have to look at overall productivity or the technology used? It will be up to you to come up with the right answers.

2. Choose the supply chain processes to automate

Not all supply chain processes may be suitable for RPA in the same way. Supply chain processes can be automated in many ways, but it is important to find the right balance between cost and efficiency.

The first process that you should automate is the inventory management process. This way, you will have a clear overview of what goods you have available and what needs to be ordered.

The second process that you should automate is the order fulfillment process. This way, you can make sure that all orders are fulfilled on time without any problems or delays.

The third process that you should automate is the transportation management process. This way, you will know where your goods are at any time.

3. Pick the best RPA solution for your needs

There are many RPA solutions on the market. However, not all of them are good for your specific needs. It is important that you do your research and find out what RPA solution will best fit your needs. A good starting point for an RPA solution is to look for one that provides you with full scalability and integration capabilities. Another important factor is that the RPA software provides the necessary security features and compliance. Above all, it is critical to start by defining your goals and objectives. In this way, you will be more confident with your options and finally invest in a great solution for your company.

4. Define the processes for managing changes

The first stages of using RPA in your supply chain management are manageable. But as time goes on, the process becomes harder. Managing changes is a difficult task for any organization. It requires a lot of time and effort. How are you going to manage it? Well, with the help of some key steps, you can achieve this in an efficient and effective way. Here are some of the key steps to follow:

1. Keeping a record that will indicate the changes that occurred and the reasons as to why they occurred
2. Responding to change quickly
3. Communicating with stakeholders about the change
4. Focusing on the desired outcome of change

Following these steps for managing change will assist the project team in making decisions and improving the quality of services and products.

5. Establish an excellence center within your company

The final step involves developing an RPA center of excellence. The ultimate goal of an RPA center of excellence is to create a collaborative and supportive environment that helps the organization grow, innovate, and continually improve. The center of excellence should also be able to deliver expertise, think strategically about the future, and position the organization for success. This will assist team members in improving how they perform their tasks and duties. It will help create a standard that every team will follow and also act as a reference point whenever they want to remember matters about RPA.

What are the Benefits of RPA in Supply Chain Management?

RPA use cases in supply chain management provide lots of benefits to businesses. It is the ultimate solution you need to better your business, whether it is online or offline. Those who have used this approach can attest to many advantages. Here are some typical benefits:

1. Boosts productivity in every department

A supply chain manager keeps track of a variety of activities that can be time-consuming to manage. RPA software and applications work faster and reduce the data workload by half, which benefits the business as a whole. Accordingly, reduced workloads by 50% result in increased productivity.

2. Reduces costs and generates savings

RPA systems correctly work in completing tasks, hence reducing the chances of errors and the need for human repetition. This in return will enhance the speed at which work is delivered and reduce the cost since the business will not have to employ more team members to perform tasks.

3. Improves customer and user experience

Customers are king in any business, and they determine its success or failure. Hence, they should receive enough attention and the best user experience. Since RPA systems reduce the workload in a business, employees can focus more on customers’ needs and deliver exceptional customer experience.

4. Achieves flexibility and speed in scaling up and down

In business, customer orders might increase at any time. This requires more employees for production to occur. Will you have to employ more temporary workers and spend a lot? Instead, you can just make use of RPA systems that can easily be scaled up and down instantly to handle a large volume of work.

Conclusion

RPA is a great solution in supply chain management, and it enables a business to scale up fast. It handles most of the back-end processes and enhances the efficiency and speed of delivery, giving more time for the team members to concentrate on providing better services to customers.

The Finance and Accounting industry is a veritable warehouse of data. Banks and other financial institutions compile and maintain paperwork that counts for gigabytes of electronic information. For instance, building a specific finance or accounting report requires multiple employees to visit the site where data is stored, make copies, and organize the information into a presentation.

This setup is very inefficient. The process consumes resources that could have been diverted to other important accounting tasks within the organization or the financial department. Fortunately, the digital age has introduced numerous solutions that could help streamline various financial and accounting processes. In other words, finance automation is now a reality.    

How Accounting Automation Can Help the Finance & Accounting Industry 

Automation can improve the efficiency of the following processes in the finance & accounting industry: 

• Accounts Payables

Accounts payable processing deals with humongous amounts of data. The sheer number of invoices alone makes the human user prone to mistakes and inconsistencies. Automation, however, avoids these shortfalls and shortens the processing time of invoice approvals.  

• Source-to-pay 

Automation can significantly shorten the turnaround time for extracting supplier invoices, gathering payment details, and forwarding the money to the vendors themselves. Automated tools are now able to access vendor emails to read invoices and gather other relevant information needed to complete the transactions.   

• Data analysis 

Before automation, employees had to pore through stacks of documents to find and then copy data for their reports. Computers reduced the amount of paperwork, but manpower still had to manually copy and paste information. With automation powered with RPA and other intelligent technologies, however, the software will analyze the data and present it according to the parameters set by the user.  

• Credit risk assessment and management 

Automation helps finance companies accurately measure a prospect’s risk and charge the appropriate interest rates, or deny financing altogether. Credit data can be instantly updated from the credit bureaus, and automated analysis can make instant decisions on approval or rejection. 

It’s interesting to think about how financial and accounting automation can be achieved. There are various methods of automating finance and accounting processes in particular. These technologies are outlined in brief below. 

Technologies used for Accounting Automation

Workflow Automation 

Workflow automation is a great way to improve the efficiency of accounting work. There are many benefits of using workflow automation for accounting. It’s not only about saving you time by automating the most tedious parts of accounting and finance processes, it’s also about saving money, improving accuracy, and generating better results.  

 

When it comes to accounting and finance, the ability to free up resources and allow employees to focus on other tasks plays a crucial role. Normally, massive paperwork and manual entry are required to be done by Accounting professionals. With workflow automation, all these time-consuming tasks are automated, run in the background, thus, freeing up time for users. Capabilities like integration with third-party systems, business logic implementation, workflow controls, and task escalation are only some of the must-have features of workflow automation software.  

Robotic Process Automation 

Scripts, macros, and bots are some of the earliest technologies used in automation since they have helped free up time and improve people’s efficiency and productivity over many years. McKinsey estimates that these early technologies are capable of automating 42% of activities in the finance department. Automation using scripts, macros and bots becomes tricky when the need to interface between multiple applications arises. In this case, there are other methods of creating and using scripts. The bottom line – all processes still take time and tie up manpower. That’s where Robotic Process Automation or RPA comes in. 

RPA is simply software that acts as a middleman between two unrelated systems. RPA, for instance, can extract the invoice data from a PDF file and then upload them directly to another system. For example, in a sales order process, RPA bots replicate human actions, send data, and create an order in the ERP system. 

RPA bots are autonomous and do not rely on a mother program like Excel to work. They can also be used by individuals with virtually no programming knowledge. Most importantly, it takes but a few minutes for a well-trained employee to create the automated process. 

Cognitive Automation 

Artificial Intelligence is the pinnacle of automation technology. AI is a piece of software that follows a preset algorithm but can make intelligent choices, within the predefined limits, involving the inputted data. This capability allows the software to perform a thorough analysis and present the data in a structured manner without errors or inconsistency.  

AI also gives way to intelligent automation. IA combines the analytical capabilities of Artificial Intelligence with the capabilities of Robotic Process Automation. The most notable implementation of IA in the finance industry is the Erica virtual assistant developed by the Bank of America. Erica is capable of analyzing each customer’s banking history and making intelligent recommendations of financial products to the user. 

Artificial Intelligence and Machine Learning algorithms constitute a great choice when there is a constant flow of data, and the decision-making process is extremely difficult and complex. Such examples include the generation of financial reports, payrolls, procurement process, analysis of employee productivity, new product launch, or predicting future churn rates. 

Summary 

All in all, time and manpower are the two crucial elements of business efficiency. A business process that ties down these two resources can have adverse effects on productivity and performance. Simple as they are, mundane tasks like data management and entry can still consume precious time and personnel. 

Finance and accounting automation enhances business efficiency by shortening the time required to perform these routine tasks. At the same time, automation also ensures that all reports generated continue to be accurate and reliable. This perk allows managers to make timely and sound decisions. Indeed, accounting automation is an asset that every financial or accounting department should not be doing without. 

Intelligent automation comes in a variety of forms and technologies (also known as intelligent process automation or IPA and hyper-automation). Intelligent automation technologies or IA is a combination of robotic process automation or RPA with a variety of other cognitive technologies. 

IA enables businesses to achieve end-to-end process automation as well as make the workflows smoother and more flexible. Hence, here are the top 10 intelligent automation technologies to keep an eye on in 2022. 

1. AI and Machine Learning 

Perhaps two of the most obvious examples that come to mind when intelligent automation technologies are concerned, are those of AI and Machine Learning. Both use digital data in combination with such elements as remote inputs and algorithms to imitate the way humans learn. 

In most cases, AI and Machine Learning are used for making predictions based on past behavior and historical data analysis. However, this field is growing rapidly and these technologies are being applied in more and more areas. 

2. Collaborative Robots 

Collaborative robots are somewhat of a new invention, but they have already established themselves as an integral part of many industries, allowing them to prevent dangerous situations in the workplace and ensure a safe environment for workers. 

Meryl Perlman, an expert from the writing services reviews site Writing Judge, says, “At the moment, there are four major types of collaborative robots: safety monitored stop, speed and separation, power and force limiting, and hand guiding. Each type has been useful in its own way and it’s great to see that such robots are still being developed and upgraded.” 

3. Semantic Software Systems 

Closely connected to Artificial Intelligence, semantic software systems and semantic technology are used to teach machines to understand data better. Semantics is encoded with the data through technologies such as Resource Description Framework (RDF) and Web Ontology Language (OWL). 

The reason why semantic technology is so important is that its fusion of semantics and data offers a variety of benefits that significantly improve the way machines process heterogeneous data sources among other things. 

4. Augmented Intelligence

As the name suggests, augmented intelligence is also related to Artificial Intelligence. To put it simply, augmented intelligence is a design model where humans work together with AI to improve cognitive performance.

The biggest benefits of augmented intelligence are connected to learning and decision-making, but the tech itself can be used in all kinds of industries. After all, it maximizes the power of human brains and AI by combining the two.

5. Process Intelligence 

Process intelligence is mostly used in business to analyze a number of processes to create a particular process model of these operations. In other words, it analyzes a particular business workflow and provides businesses with insights into it. 

With the help of process intelligence, you can detect problem areas in your business processes and significantly improve your operational model. Such analysis is particularly useful for businesses that rely on non-linear processes that make it harder to accurately analyze the entire workflow due to the number of dependencies. 

6. Process Mining 

Process mining is both a part of IA and process management. The primary aim of process mining is to support operational process analysis by using so-called event logs. It’s meant to show what humans, machines, and entire organizations are actually doing. 

7. Natural Language Processing (NLP) 

Also known as NLP, natural language processing is a branch within the more general fields of AI, computer science, and linguistics that is closely connected to IA. NLP focuses on the interactions and interrelations between computers and the human language. 

More specifically, NLP is used to understand how computers should be programmed to process and analyze natural language data. NLP usually works with large amounts of such data which is precisely why it is so valuable. 

8. Computer Vision 

Computer vision is considered to be a field within IA that is concerned with enabling computers and entire systems to extract useful and relevant information from digital sources. Such digital sources can range from images to videos to other types of visual inputs. 

Based on the extracted information, recommendations can be made both for further actions and for general assumptions or conclusions. In this sense, computer vision is essential for interpreting and understanding the visual world as well as making such interpretation possible for machines. 

9. Optical Character Recognition (OCR) 

Also referred to as OCR, optical character recognition includes either electronic or mechanical conversion of images from typed, handwritten, or printed text into machine-encoded text. Due to this, OCR is sometimes referred to as an optical character reader. The conversion usually involves certain types of materials such as scanned documents, photos of documents or scenes, textual subtitles on images, and so on. 

10. Robotic Process Automation (RPA) 

Last but not least, robotic process automation (also known as RPA) is a kind of software technology used to operate and manage software robots. These, in turn, are used to mimic human behavior when interacting with digital systems and software. 

For example, such robots can simulate repetitive human actions, predict results, classify behaviors, scan documents, identify content and enhance the decision-making process. 

Conclusion 

All in all,  intelligent automation technologies are definitely on the rise now and keep helping businesses innovate their processes. It’s a good idea to pay attention to the latest developments in the field of IA to understand how such technologies work and how you can use them to pursue your own goals. 

Whether you are more interested in robotic process automation or you already have some experience in natural language processing, learning about all of the IA technologies will give you a better understanding of the field as a whole. 

 

Businesses require consistency and predictability. Without those essential factors, an organization is forced to operate with uncertainty and a lack of reliability, neither of which are conducive to business sustainability. However, attaining consistency and predictability within a business is not easily done, which is why any business concept, that helps achieve that, must be actively considered. Business process flows are an excellent example of such a concept. They are a practical way of ensuring that two essential things are achieved in any process: focus and consistency.

This article will provide an overview of the definition, the principal benefits of business process flows, and the simple steps to create successful business process flows. 

Process Flows in Context 

At its simplest, a business process flow is the sequential representation of a process and the various components thereof. These components can include operational factors such as actions required and the people and resources needed to achieve them, as well as applicable timelines. It helps define and layout all the aspects of a business process, so that said process is easily understood. One could say that a process flow provides a ‘snapshot’ overview of a given process. It allows employees to have a good understanding of how a business works. 

Importantly, a process flow can be devised for any type of work or process in any type of organization. Therefore, a process flow can be as effectively used to describe how a purchasing order should be processed by the finance department, as it can be by a sales team to pitch a new product to potential customers. Process flows are used by industries as diverse as software development, auto assembly, and healthcare management. Below is a standard template for a process flow that can be used by a company’s to automate HR-related processes like the onboarding case: 

As can be seen in the process flow diagram above, a business process flow provides a breakdown of the various inputs and outputs within a process. Each of these workflow components is usually denoted by means of shapes, typically ovals, diamonds, and rectangles, with each being connected by lines that indicate the possible paths. The ‘flow’ within a business process flow and workflow design usually follows an A to Z logic, i.e. from commencement or start of a process to its logical conclusion or end-goal, whatever the latter might be. 

Benefits of Business Process Flows 

There are many benefits to having process flows, including process mapping, the principal ones of which include: 

• Communication: everyone can understand a specific process, and be trained accordingly. 
• Standardization: processes can be reliably replicated. That is why they should be an integral and invaluable part of standard operating procedures (SOPs).
• Comprehensiveness: process flows can be established across all verticals and at all levels within an organization. 
• Maximization:  all resources can be used to their full potential. 

 There are also systemic benefits to having business process flows in place: 

• Cost minimization: understanding exactly how processes work means that cost efficiencies can be implemented where possible. 
• Risk management: understanding your process means being able to identify potential risks and better able to mitigate them. 
• Agility: process flows should ensure fewer (or no) bottlenecks, errors, and duplications, making for a more Agile business. 
• Continuous improvement: knowing each step of a process means being able to improve processes as needed. 

These benefits are applicable to process mapping itself, which is the actual diagrammatic compilation (i.e. mapping) of a process and its various components. 

Simple Steps to Create Process Flows 

The beauty of process flows is their simplicity, however complicated or technical the actual process might be. As such, simple steps can be taken to ensure that your process flow will be effective: 

Step 1: Name it – the process flow should be specifically named according to the naming conventions used by your organization. 

Step 2: Give it a purpose – what is the intent of the process flow? Why is this specific process flow in place and to what end? 

Step 3: Scope it – give the process flow the needed extent of the scope by asking a simple question: what inputs and outputs should be included and excluded? 

Step 4: Map inputs and outputs – go through each stage/phase/level of the process and identify the required inputs and outputs for each. Be specific in the inputs and think of possible variables for outputs. 

Step 5: Provide direction – a process flow should comprise a series of directional arrows based on ‘Yes/No’ or ‘What If/What Then?’ questions posed that help connects inputs and outputs (i.e. components within the process flow). 

Step 6: Assign duties and responsibilities – where needed in the process flow, applicable responsible people or line management should be indicated. 

Step 7: Make it visual – a process flow should be mapped and its diagrammatic representation/workflow diagram to be readily available to any person who may need to understand the process and its objectives/intent. 

A final point: consider workflow automation powered with RPA and AI/ML capabilities of your business flows: Robotic Process Automation (RPA) is already being used by many businesses to enhance and automate repetitive process flows. RPA software can be used in order to choose which processes in a business should benefit from automation. Sales ordering process, enterprise resource planning (ERP), customer service, and payroll are just four examples of typical processes that can benefit immensely from Robotic Process Automation. 

Conclusion

In today’s fast-paced and competitive world, organizations are constantly looking for ways to increase their efficiency and reduce costs. Business process flows are a critically important means by which a business can give itself the structure and sense of purpose needed to succeed. Process flows can help foster transparency, enhance collaboration, and create business intelligence.

Comidor workflow automation platform allows users to design any type of business process flow, automate and optimize workflows end-to-end, and incorporate intelligent automation functionalities, like RPA, AI, and Ml. There are many benefits associated with Comidor. It can help organizations save time by automating tasks, enhance customer service, and improve company culture through transparency.

In closing, value-adding performance by management and employees alike don’t just magically happen. It is the culmination of intelligent automation decisions made and actions put into practice. The real magic is in being able to ensure that business processes are created appropriately and work as planned again and again. 

Author bio
Bryan Christiansen is the founder and CEO of Limble CMMS. Limble is a modern, easy-to-use mobile CMMS software that takes the stress and chaos out of maintenance by helping managers organize, automate, and streamline their maintenance operations. 

For businesses facing exponential growth, automation is the ideal solution for meeting increased demands. Fortunately, there are countless software tools available that can lead to the inevitable automation of entire business processes.  

These tools incorporate state-of-the-art technologies such as Robotic Process Automation, Machine Learning, and Artificial Intelligence. Collectively, they lead to the Hyperautomation of businesses. Separately, they achieve specific automation goals.   

So, what exactly is the difference between Robotic Process Automation vs. Machine Learning? And what about Artificial Intelligence vs. Machine Learning? These tools may all come together to achieve Hyperautomation, but what truly makes them unique? We have the answer to all of these questions and more. Read on to learn more about RPA vs. Machine Learning vs. AI.  

What is Robotic Process Automation? 

Ever wished there was a software that could handle all those repetitive tasks on your to-do list? Well, there is! Robotic process automation (RPA) is an automation technology that implements, and manages robots. These robots can complete routine tasks without needing human touch. Anyone in your business can use RPA software to deploy robots that will mimic human actions throughout a business process.  

What is Machine Learning? 

Machine Learning (ML) is all about data and algorithms. Instead of spending time inputting rules for Machine Learning, this technology uses real-time data to predict the next step in the process.  

Using the data available, Machine Learning will create a model of the typical workflow pattern and begin to improve the algorithm based on common relationships and historical data. In a sense, Machine Learning understands how humans act and mimics that method.  

What is Artificial Intelligence? 

Artificial intelligence (AI) is a widely-known technological area. AI is a set of technologies used to help machines understand how humans think. Once these machines understand the human mindset, they are able to complete tasks in place of humans. This technology is widely used in automation software as a way to check routine tasks off a to-do list without needing to spend time in your day doing them yourself.  

Now that we understand what exactly these tools are, we’ll take a look at the similarities and differences between Robotic Process Automation vs. machine learning vs. artificial intelligence.  

RPA vs. Machine Learning vs. AI 

Though these tools sound highly similar, there are key differences between RPA vs. Machine Learning vs. AI that make investing in all three worthwhile.  

Similarities 

To start, let’s discuss the obvious: how they’re similar. All three of these software tools are used to mimic human action in order to complete routine tasks and speed up business processes, especially for small businesses with limited resources.

Combining these tools together can assist a business in achieving intelligent process automation. This automation allows businesses to make progress toward a total digital transformation, in which they rely heavily on technology to complete tasks, finish projects, and keep customers happy.  

Additionally, Machine Learning and AI are closely intertwined. In fact, Machine Learning is actually a subset of AI. Machine Learning uses AI’s process to understand the relationships between tasks and learn on its own how to mimic those tasks.  

Differences 

Though each of these tools is an essential part of automating repetitive tasks, they each serve their own function. The differences between RPA vs. Machine Learning vs. AI are: 

• Rule-based vs. data-based. Both machine learning and AI are driven by data. RPA, on the other hand, requires rules input by humans to function correctly.  
• Programming. Since RPA needs rules to function, it requires human programming to start completing tasks. AI and machine learning will use data and algorithms to understand how to function and, therefore, do not need much human interaction.  
• Process improvement. If your RPA software is not functioning in a way that works for your team, you’ll need to manually change the rules and allow your software time to adjust. With AI and machine learning, the algorithms will automatically update as new data is discovered to better meet your business needs.   

Each tool is able to complete different tasks using its own methods. That’s why it’s essential to integrate all three into your business if your goal is to achieve Hyperautomation.  

Integrate Agile Hyperautomation with Comidor 

The question is not whether you should choose between Robotic Process Automation vs. Machine Learning vs. Artificial Intelligence. Instead, it’s how quickly you can integrate these systems into your business and start automating tasks.  

With Comidor’s array of Hyperautomation tools, you can have your routine tasks completed in a very short time! Comidor offers Business Process Management (BPM) software that, when combined with workflow automation and RPA, ML, and AI, can ensure that your business has all the necessary tools to achieve agile digital transformation.   

Request a demo today to learn more about how Comidor can help you achieve the Hyperautomation your growing business needs to thrive!