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How Automation ROI Can Pay For Your Business Objectives

By Automation Initiation No Comments

The most compelling reason to introduce automation into your business is actually a hidden one: automation ROI can pay for your business objectives. Any business intending to undergo a transformation or implementation project will understand the significant costs involved. From the software costs to change management, projects like these are an expensive but necessary venture to drive growth. But not all businesses can easily fund their strategic objectives. This is where automation holds the key. This post explains how automation can be used to fund your business objectives and save you money.

Automation ROI

The core driver behind automation is the ‘Automation ROI’. This is calculated as the benefits you can expect from automating a particular process. The calculation is:

(Number of Time Process Is Run Per Month)*(Length of Time Process Runs For In Minutes)*(12/60)*(Avg. $ Cost of Running Process Per Hour)

For example, a business may have an invoice processing process that is run 60 times a month, usually takes 30 minutes, and pays staff on average $40 per hour. The Automation ROI for this would be:

(60*30*12/60*40) = $14,400

This means that by automating this process you effectively get back $14,400 per year of staff time that you can re-invest into the business. This would also not be the final-result as further ROI can be generated from automating additional processes with the spare capacity of the automation.

Funding Your Business Projects

Businesses that want to grow will typically undertake a variety of big projects including:

  • CRM upgrades
  • ERP implementations
  • Document management system migrations
  • Product research and development
  • Datawarehouse implementation

These projects will come with significant costs attached including disruption and staff retraining. Many businesses overlook these costs, and inevitably end up paying more, as these projects have a tendency to go sideways or suffer delays which ultimately adds up to wasted time and money. But, we can cleverly use the money that we have saved from automation to pay for these costs. For example:

  • Business ‘A’ wants to upgrade their CRM
  • Analysis has indicated that this project will take 3 months to complete.
  • The costs of disruption to the business, staff training and change management have been estimated to amount to $25k.
  • An ‘Automation ROI’ analysis indicates that automating the existing customer mail triaging process will yield savings of $25k.
  • Therefore, by automating the customer mail triaging process, you can effectively fund the CRM Upgrade project at no additional cost by using the savings you have made to offset the expected costs.

This is how smart businesses are approaching all their growth-focused projects – by examining where they can obtain money from within the business already and using that to pay for business objectives.

 How Do I Start Saving

To start paying for your business objectives, you have to:

  1. Outline the business objective you wish to achieve (eg implement a data platform to capture and serve financial information)
  2. Calculate the staff costs involved (eg staff will need to be involved in UAT, retrained etc.)
  3. Identify candidate processes for automation (eg processes that finance staff do and would benefit from being automated)
  4. Calculate Automation ROI
  5. Determine if the Automation ROI matches the staff costs

This method can be applied across the business and for every project. Once you get into the habit of performing the analysis, you can effectively plan your objectives and actively commence your important growth-driving projects knowing that you have secured funding to pay for the anticipated costs.

If you want to know how to pay for your business objectives, please contact us.

PowerBI Deployment Whitepaper

By Enterprise PowerBI No Comments

In this PowerBI deployment whitepaper excerpt, we discuss how deploying PowerBI at scale presents a range of issues. Much of it comes from how an organisation grows. Setting the time aside to address the nascent issues is not important in a business’s early life, nor is the impact of them apparent enough to make them worth addressing. For less experienced executives there are the pitfalls of not even knowing there are issues building up. Often gaps can be patched with a bit of human ingenuity, effort – and of course – Excel.  In our view there are four key issues that converge to lead to common mistakes and wasted costs.  


PowerBI deployment challenges

PowerBI deployment challenges


First is access. Working with data is often viewed to be something best left to specialists, propeller head techies or the “number crunchers” in finance. Workers are left data illiterate and dependent on someone else to do the work – and thinking – for them. Scary, weeks long self-study technical courses reinforce this idea. What is usually needed is content and training targeted to the audience. An executive may just need 5 minutes of focused education on a dashboard pertinent to them, and only the analyst will need the weeks long course.  

Second is quality. Systems have improved significantly in their ability to filter their front-end input so that the correct types of data are captured, but still users find a way to enter data in the wrong place, format or not at all if it doesn’t help them complete their task. More challenging in modern environments is the array of systems involved that simply don’t relate to each other at scale. A frontline worker may remember all the different codes that relate to a given customer or product, but a bulk data analysis system does not and is unable to relate them. Good data quality is recognised in the literature as one of the key factors in ensuring a successful implementation alongside governance of that quality.  

Third is discoverability. Even in only moderately complex organisations data is used, reused & recycled with next to no traceability. This leads to duplicated effort, inconsistent definitions, that then drives contention within the business as people disagree over what is the right way or measuring progress. Access is also often siloed, with line of business or system owners being protective over what they see as their data, wary of how others may interpret it.  

Last is governance – a polite way of saying ownership and management of data. People in the organisation need to care for, manage and nurture their data – KPMG state that “Data is now the most significant asset many organizations possess” – and as such needs to be cared for – but like all intangible things it is easily forgotten about. Businesses that are prepared to put a value on that asset are few and far between, and most often only realise its value when a core system experiences an outage. 


This is an excerpt from our Enterprise PowerBI Whitepaper – please follow the link to read all the content – it’s free & there’s no sign up required.

Need help after reading this piece of our PowerBI Deployment Whitepaper? At Talos we have defined our PEBBLE Enterprise PowerBI Methodology to help organisations drive success in deploying PowerBI as a complete self service analytics platform. If you are struggling with any of the challenges discussed above, we might be able to help. Please get in touch if you’d like to have a discussion.

Cheers, James

BI Challenges

By Enterprise PowerBI No Comments

Do any of these BI Challenges sound familiar? Does your business run on high risk, ungoverned spreadsheets that nobody apart from their original creator really understands? (Boldly assuming they are still with your organisation). Do you frequently clash with your peers over who has the right version of the numbers? Is there a team of analysts and number crunchers beavering away to produce figures each month? Is that team duplicating effort by other departments? Do you even know if they might be? Do your peers readily share their data?

All these issues are common throughout modern businesses despite the means of eliminating them being readily available. There are of course huge benefits to be obtained by becoming a data driven organisation which is why many industries invest significantly in being able to use their information to improve their business.

Benefits of being Data Driven

Benefits of being Data Driven

Getting its house in good order and overcoming these BI Challenges allows an organisation to quickly realise the benefit of simply having reporting happen automatically, instead of being a panicked, last-minute activity for already overburdened analysts. This frees up the analytical capability of the business to use analysts to add greater value by identifying the opportunities and risks that data can reveal.

Leaders then can realise the benefits of having a 360-degree view of the organisation – from sales through to productivity – and change the track of business in real time, instead of waiting for a report with data from the last quarter and trying to correlate that with others in a mental juggling act. Finally, the improved window on data quality allows the data to be improved to the point where it can support automation within the business – another key pillar for Efficient Decision Making. Leaders are often uncertain of how to quantify the benefits from undertaking these often-challenging activities, but if you simply look around, the Financial Services sector is a heavy investor in this space, and let’s face it, banks aren’t going to be investing if there isn’t a good ROI.

Data and analytics veterans often express a degree of frustration that we are still trying to solve the same problems we were decades ago. However, most of us have come to accept this is how businesses grow and mature in their information usage. Some of these steps are virtually inevitable as an organisation grows in capability, complexity, and capacity. Gartner’s Information Management Maturity Model has been in existence for 20 years describing exactly this journey

BI Challenges described by the Gartner Information Management Maturity Model

Gartner Information Management Maturity Model

There are few shortcuts to solving these BI Challenges, but the difficulty level has been decreased in recent years. So, what has changed to make these problems more solvable? Simply, the evolution of user friendly, cloud based, pay by usage data & analytics technologies has massively lowered the barriers to entry. The ability to start an enterprise grade journey has stopped being an expensive up-front expenditure and is now – in theory – something any organisation can do.

This is an excerpt from our Enterprise PowerBI Whitepaper – please follow the link to read all the content – it’s free & there’s no sign up required.

At Talos we have defined our PEBBLE Enterprise PowerBI Methodology to help organisations drive success in deploying PowerBI as a complete self service analytics platform. If you are struggling with any of the challenges discussed above, we might be able to help. Please get in touch if you’d like to have a discussion.

Cheers, James

UiPath & Azure: Data Driven Efficiency

By Automation Initiation, Data Platform, Enterprise PowerBI No Comments

At Talos our goal is simple: to deliver data-driven efficiency. In our experience, the best way to achieve this technically has been through the combination of UiPath & Azure – two very powerful technology stacks that when paired properly will deliver immense value. This blog post examines the relationship between UiPath & Azure, a typical design & use-case, and the data driven benefits of leveraging both together.



UiPath & Azure

UiPath is the world’s leading RPA company delivering a suite of automation technologies targeted at the enterprise level. Azure is Microsoft’s cloud platform, offering a vast array of services to customers to meet their complex needs. Given the technical strengths of each, it is possible to craft a solution that utilizes both to achieve optimum benefits, and in our case, deliver our goal of data-driven efficiency.

In numerous projects we have worked on, there has been a typical requirement to deliver reporting based on the combination of data from a variety of sources. This simple use-case can actually be quite complex, especially when dealing with legacy data source systems, large volumes of data and a significant reporting consumer-base. However, these requirements can be met with a very straight-forward UiPath & Azure solution design:

UiPath & Azure

This design is composed of the following individual elements:

  1. Azure VM’s
    1a. UiPath Studio
    1b. UiPath Unattended Bot
  2. Azure Blob Storage
  3. Azure Data Factory
  4. Azure DevOps
  5. Azure SQL Database
  6. Power BI

Each of these elements have a specific role in the solution, and fit in easily with each other, making this solution extremely robust, easy to initiate and  scalable.

  1. Azure VM’s

Azure Virtual Machines (VM) are the image service instances that provide computing resources that behave exactly like physical infrastructure, except virtually. The benefits of Azure VM are the on-demand nature of the product and the lower costs associated with management. In our solution, 2 of these VM’s are commissioned to provide separate environments for the UiPath tool:

1a. UiPath Studio is installed on the first VM (this is used as the dev/test environment). UiPath Studio is the development tool used to create and test automations. In our case, we use UiPath Studio to develop the automation steps required to retrieve data from the different legacy systems.

1b. UiPath Unattended Bot is installed on the second VM (this is used as the production environment). Once the automations are developed and tested, they are deployed to be executed by the Unattended Bot on this VM. By having a dedicated VM, this bot acts like a 24/7 worker and is available on the VM to perform any tasks it is instructed to do.

  1. Azure Blob Storage

Azure Blob storage is the scalable and secure object storage service used to store data in a variety of formats. Blob storage is very robust and can scale very easily to suit storage needs. In our case, we leverage Blob storage as a staging area for the bot to store the data it has retrieved, and also serves as a source for the Azure Data Factory pipeline later on. UiPath can communicate with Azure Blob storage natively, making this integration easy and reliable.

  1. Azure Data Factory

Azure Data Factory (ADF) is the data integration service built for complex ETL projects. The benefits of ADF are the ease-of-development as well as the powerful capabilities that allow it to handle complicated data transformations in large volumes. In our case, we use ADF to create a pipeline to move data from Blob Storage into the Azure SQL database, whilst performing sophisticated transformations. Although UiPath possesses some ETL functionality, they lack the advanced capabilities of ADF regarding transformation and speed. For this reason, ADF is a must have in our solution.

  1. Azure DevOps

Azure DevOps (ADO) is the collaboration tool for software development offering work tracking, source control and continuous integration/delivery. ADO allows projects to be managed effectively and collaboratively. In our case, ADO acts as the project management tool and code repository for the ADF pipelines. Although UiPath has a native integration with ADO, it also possesses the source control and deployment capabilities out-of-the-box, and therefore can be managed within the tool itself.

  1. Azure SQL Database

Azure SQL Database (DB) is the cloud-based database service built on the SQL Server engine. It has a wide range of deployment options, making it very easy and effective to manage. In our case, this is where the transformed data is stored and made available for analysis. The scalability, availability and deployment ease of Azure SQL DB make this very attractive for enterprise-level analytics and reporting.

  1. Power BI

Finally, whilst not an Azure service itself, Power BI is used as the reporting tool to develop custom reporting on the data in the Azure SQL DB. Power BI is an excellent reporting platform for enterprise-level reporting due to its scalability and self-service capabilities. With this tool in place, the data is modelled and reported to the business.

Although every project is different, the above represents a good design for a typical solution and is used by us as a list of ‘minimums’ that we need. For our work, this design is very common, but is also great as a default because it can be restructured very easily to suit any additional needs (for example adding Azure Machine Learning can be integrated into the above design as part of a CASSIE deployment). With the above solution, a business can very quickly leverage the benefits of UiPath & Azure working in unison and delivering data-driven efficiencies: businesses are able to get the insights and reporting they need without having to expend any staff time to deliver it.

If you want to know more about UiPath & Azure together, please contact us.

Invoice Processing: The Case For Automation

By Automation Initiation No Comments

In the context of business administrative activities, invoice processing is the single most important process to get right. These activities ensure that business operations run smoothly without delay or difficulty. As we have seen before, a slow and unreliable process in the accounts payable department will inevitably contribute to inefficiencies across the wider business, costing both time and money. It’s no coincidence then that there has been an explosion in interest in automating invoice processing. On paper, the advantages of automation such as speed, accuracy and reliability, should work well for invoice processes. Through our work with various businesses, we have been testing this hypothesis – and the results are in. Automation is an absolute necessity. This blog post examines invoice processing in detail, the benefits of invoice automation and how to quickly automate your invoice processes.

Invoice Processing

Invoice Processing

Invoice processing refers to the tasks and activities that businesses perform to ensure that invoices are received, recorded and acted upon in a reliable and timely manner. This process is perpetual – new invoices are received virtually every day and must be actioned immediately to ensure that obligations are met. Typical steps involved include:

  • Receiving invoices in a central location (eg mailbox folder)
  • Validating that the invoice is correct (eg 3 way matching)
  • Recording the data into a system (eg entering the data into an ERP)
  • Confirming receipt of the invoice (eg generating reporting on new invoices)

The details of each task are likely to be different in every business, for example the logic used to validate that an invoice is correct may rely on different factors such as amount thresholds etc. However, the steps remain the same for every business – an invoice is received, recorded and reported.

When comparing invoice processing principles to automation benefits, it becomes clear that automation is a good fit:

  • Processing is speed sensitive –> bots are quicker at performing tasks than humans
  • Processing relies on accuracy –> bots do not make mistakes or ‘human errors’
  • Processing must be timely –> a bot is a reliable, ‘24/7’ worker

Invoice Automation Benefits

After automating your invoice processing, the obvious benefits you can expect include:

  • Happier suppliers, as their invoices are processed quicker and are not missed
  • Happier staff, as they are no longer performing this low-value task
  • Better cashflow management, as you are recording invoices quickly and more accurately, allowing you to plan finances ahead of time
  • Reduced risk of unexpected expenses due to mishandled invoices

The above benefits are the most common. However, depending on your business, there are some other features to automation that may be beneficial:

  • Invoice processing in your business may be more complex and require stages of approval. Automation technology, particularly UiPath, make it very easy to design a hybrid-process, whereby a bot performs certain tasks and hands it off to a human for approval. This combination of human and bot has the effect of augmenting each other and can deliver greater efficiency.
  • Before undertaking an automation project, a careful review of the existing processes takes place. During this phase, it is not uncommon for businesses to identify issues or inefficiencies in their processes, especially if the process is either very new or very old. After identifying these issues, businesses can take action to improve them, and drive further efficiencies.

How To Automate Your Invoice Processing

The key with automating your invoice processing is to define your process in detail. This includes all the systems involved, the steps performed, the logic used and the possible exceptions that may arise. Once you have defined these, the actual work in automating the process becomes much easier. In fact, having gained significant experience with invoice processing, Talos has designed and released ROBBIE – our Robotic Invoicing Expert. So much of our work has been in delivering a common invoice processing solution, that we have developed a bot that can learn any invoice process quickly and execute it reliably. ROBBIE has been trained to specifically work on invoice processing and is already in use across Australia. If you want to get started, deploying ROBBIE in your business is quick and easy – better yet, he can start working immediately and returning value in your business.

If you want to know how to automate invoice processing, please contact us.