Is Your Accounting Solution Helping or Hurting?

Accounting solution  

This is the first in a three-part series where we address the main hurdles facing finance today, and identify some tools and technologies that can help you overcome these hurdles.

Gone are the days when finance leaders were simply bean counters. As a finance leader, of course you must take on the responsibility for the integrity of the transactional reporting for the business, but you also must think and act more strategically. You must navigate the uncharted waters of the global, digital economy and guide the business towards increased growth and profits. You can’t do it only by looking in the rearview mirror, and you can’t do it if your hands are tied by old accounting systems based on outdated technology.

We know that finance leaders tend to be a conservative bunch and you think long and hard before you invest in anything that doesn’t directly produce revenue. If you already have an accounting solution and it’s not broken, then there’s no need to fix it, right? Actually, you could be dead wrong.

Old Perceptions Linger

For decades replacement of solutions that are used to run the business have been likened to brain surgery. You don’t do it unless the patient is dying. “Rip and replace” was to be avoided at all costs. But these perceptions are just as outdated as the legacy solutions to which they apply. Yes, early solutions were rigid and inflexible, limited in functionality, hard to install and implement and even harder to use. Innovation was painfully slow due to rigid architectures and older technology. Why go through all the blood, sweat and tears, not to mention the cost, of implementing a newer solution just to wind up right back where you started?

So, have solutions really changed that much? The answer is a definitive, “Yes!” Those older solutions may have once been state of the art, the best of the best available at the time. But they simply can’t compete with modern applications today. Solutions now are far more flexible and technology-enabled, provide many more features and functions, are easier to install, easier to implement and easier to use.

What Does Prompt Replacements?

We asked the survey respondents to our 2019 Enterprise Solution Study to check off all the different reasons that might prompt them to replace their current solutions (Figure 1).

Efficiency is at the very top of the list – the need to do more without adding headcount. This follows the trends in today’s workforce. We’re all asked to do more, and we would like to accomplish this without working longer hours.

Figure 1: What would prompt you to replace your current solution?

Is Your Accounting Solution Helping or Hurting?

Source: Mint Jutras 2019 Enterprise Solution Study

The second most often cited reason prompting a search for a new solution is one that should resonate with finance leaders – the creation of a cost advantage. Is your IT staff spending all of its time just keeping the lights on, rather than contributing at a more strategic level? There’s also the cost of obsolescence. Replacement of outdated technology can save in terms of maintenance, both preventative and remedial.

But in order to produce these cost savings, you need the kind of advanced technology that sets today’s modern solutions apart from those legacy solutions. So, while “Outdated technology is too limiting” ranks third in our survey, Mint Jutras would argue that it should be first and foremost. The fact that it is not is indicative of a general lack of understanding of what these new technologies can do for you.

Advanced Technology Holds the Key

Table 1 lists several technologies that are embedded in finance systems today.

Table 1: Perceived Value of Embedded (or Foundational) Technologies

Perceived Value of Embedded (or Foundational) Technologies

Source: Mint Jutras 2019 Enterprise Solution Study

While a growing percentage of respondents perceive these technologies as providing strong value, on average 30% are unsure of the value. Essentially, they are saying, “Show me.” And another 10% (the average across all) simply don’t know. And therefore, it falls to industry experts and the vendors themselves to educate their audiences in order to prove the value. Let’s start that process by exploring a few of these.

Platforms and Architecture

Development platforms and microservices architectures, on which applications are built, are the perfect example. For the reader with a technical background, a microservice architecture is defined (by Wikipedia) as an architectural style that structures an application as a collection of loosely coupled services. For those nontechnical readers, think of it as constructing a solution from a set of Lego building blocks.

Think about how you build a structure from Legos. Each Lego block is made of the same kind of material and is attached (connected) to the other Lego blocks the same way. In many ways they are interchangeable. But by choosing different colors and sizes, and connecting them with a different design, you can make a structure that is very unique. And once constructed, if you want to change it, decoupling some of the blocks and replacing them doesn’t destroy the parts that are not affected. There is far less disruption introduced than if you had constructed it with a hammer and nails.

Today’s modern technologies support this approach by creating solutions as components rather than a single monolithic line of code. New components can be added as extensions or used to replace existing components without having to invasively modify that monolithic structure. By taking a platform approach, modern architectures support loose coupling of these extensions by providing APIs (application programming interfaces) that negate the need for invasive customization and also facilitate integration with other applications.

This component-based approach can also be applied to implementation, allowing you to execute it more incrementally… and strategically. It provides a level of agility, configurability, and extensibility to today’s applications that help us respond to growth and change.

Artificial Intelligence

Technologies like robotic process automation (RPA), machine learning (ML), natural language processing (NLP) and other forms of artificial intelligence (AI) have become quite prevalent in consumer technology (think Siri and Alexa, or GPS that learns your favorite route). Now is the time to bring them into the enterprise, much like they were insinuated into our personal lives – by adding value and embedding them.

Make no mistake – all sorts of artificial intelligence technologies are coming to the enterprise, but you won’t be able to take advantage of them if you are still stuck on old legacy solutions.

Predictive and Cognitive Analytics

All solutions today can present data to you. Predefined reports help you answer relatively static questions like: How much did I sell by customer type or region? Analytics present the bigger picture and can help you figure out what questions to ask like: Where and how will I have the most success in regaining and /or growing revenue? In your quest to answer that you might ask: Are all sales down, or only by region or customer type or sales rep or product? This might take several iterations and the exact path you will take in your questioning won’t be apparent until you start to drill down. Combining analytics with artificial intelligence makes that process (and you!) smarter.

Predictive analytics is all about detecting patterns and scoring probability, most typically in terms of measuring risk or opportunity (think predicting cash flow or forecasting demand). Algorithms are created that can make suggestions and/or automate decision making processes and continue to learn over time. This takes more cognitive capabilities. Fully understanding and utilizing the growing volumes of data, at a level that is granular enough to make a difference, taxes the cognitive capabilities of even the most astute human. The technology that can add cognitive capabilities to enterprise applications is no longer the stuff of science fiction. This is really what machine learning is all about – getting smarter over time without a human directing the learning process.

Wrap Up

For decades these types of implementations have been compared to brain surgery. You just don’t do it unless the patient is dying. That was understandable when solutions were rigid and inflexible, limited in functionality, hard to install and implement and even harder to use. With today’s technologies though, making a change is not as difficult as you may think. Solutions now are far more flexible and technology-enabled, provide many more features and functions, are easier to install, easier to implement and easier to use. Don’t wait until the patient is dying before you make a move.

This article originally appeared onSage Intacct.

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