Monthly Archives

May 2024

Planning for the Successful Transition to New Accounting Software

By | Accounting, Accounting Software, Nonprofit | No Comments
person using accounting software on laptop and mobile phone

Perhaps your organization has outgrown spreadsheets or off-the-shelf small business accounting software. Now, it’s time to find government fund accounting or nonprofit fund accounting software. The platform of your dreams has all the bells and whistles you’ve hoped for: great budgeting features, invoicing and automation, and super reports.

As you prepare for the implementation of your new accounting solution, there are several steps you can take to prepare your data and your team for the transition to the new platform. With these steps, you’re more likely to have a successful transition to your brand-new accounting software.

Clean Your Data

The data that’s currently in your system, whether you’re using spreadsheets or a small business accounting program, will move into the new system to get it started. If there are mistakes or errors in your current system, now is the time to correct them.

Cleaning data refers to the process of identifying and correcting errors, inconsistencies, and inaccuracies in a dataset to ensure its accuracy, completeness, and reliability for analysis or other purposes. This process involves several steps, including identifying errors, handling missing data, removing duplicates, and standardizing data. Additional steps may be resolving inconsistencies and developing what is called a “data dictionary” or a standard guide to data inputs.

Consider your donations for the past year, for example. Perhaps you input donor names and addresses into a database, spreadsheet, or your old business accounting program, and now you want to move it into your new accounting database. Checking to make sure there are no duplicates is a smart idea. Duplicates may not be exact matches, so you may need to work with your team to generate lists and manually check them. (For very large data files, there are companies that specialize in data cleanup.) Common places where duplicates creep into files include:

  • Addresses where road, street, or avenue are spelled out—and a second address where it is abbreviated. You’ll need to decide what the standard for your organization will be—the postal abbreviation or spelling out the full word.
  • Names where a first initial is used (J. Smith), fully spelled out (John Smith), or includes a middle initial (John A. Smith). You’ll have to decide which John Smith version to keep.

These are just two examples of some very common areas where duplicate records can occur. Other places to clean up before exporting your data to move it into the new system include reconciling bank accounts and credit cards, updating A/P and A/R, and ensuring other financial information is updated and accurate.

Document Procedures and Workflows

The accounting and finance team should document common processes, procedures, and workflows. This is important because your new accounting platform may include ways to automate steps in the workflow. It is also a good time to dust off any procedures you have already written out and update them if necessary.

Some examples include:

Donation Processing Workflow

  • Receiving donations via various channels (online, mail, in-person).
  • Recording donor information and donation details.
  • Issuing donation receipts or acknowledgments.
  • Allocating donations to specific programs or funds (if applicable).
  • Reconciling donation records with bank deposits.

Program Expense Allocation Workflow

  • Allocating expenses to specific programs or projects.
  • Tracking program-related expenses separately from administrative and fundraising expenses.
  • Ensuring expenses are allocated in accordance with donor restrictions (if any).
  • Reporting on program expenses to stakeholders, including donors and grantors.

Other common nonprofit workflows include grant fund management, compliance reports, and general financial reporting.

By documenting frequently used workflows on paper, you’ll be in a much better position to understand how the same process works in your new accounting platform. Working with your software vendor or consultant, you can set up the workflows, ensure the reports you need are ready, and be better prepared for the new software.

Work with a Skilled Nonprofit Accounting Consultant When Installing New Accounting Software

It’s vital to get your new accounting software set up, and the data moved into it correctly. This is an area where having a skilled and experienced nonprofit accounting software consultant is vital. With the right consultant by your side, the transition to your new platform will be smoother and easier. You’ll be up and running in no time, with the right automations in place for maximum efficiency so you can better manage margin to support your mission.

Welter Consulting

Welter Consulting bridges people and technology together for effective solutions for nonprofit organizations. We offer software and services that can help you with your accounting needs. Please contact us for more information.

How CFOs Are Utilizing Machine Learning

By | Accounting, Nonprofit | No Comments
CFO using computer, showing AI on monitors

You can’t open a professional journal, website, or news site these days without seeing articles about artificial intelligence (AI). AI, in all its many forms, offers exciting potential to many professions, including accounting. Machine learning is one branch of the overall AI “tree” that continues to expand in many directions, including Generative AI, machine learning, natural language processing, and more. In this article, we’ll help you better understand machine learning and share examples of how CFOs are tapping into the potential of this new technology.

What Is Machine Learning?

Machine learning is a branch of artificial intelligence (AI) that involves the development of algorithms and statistical models that enable computers to progressively improve their performance on a specific task through experience or data. Instead of being explicitly programmed to carry out a certain task, machine learning algorithms learn from patterns in data, allowing them to make predictions or decisions without being explicitly programmed for every scenario. Machine learning techniques are widely used in various fields such as image and speech recognition, natural language processing, medical diagnosis, financial forecasting, and many others.

Machine learning works best when there are predictable, stable patterns and large amounts of data the system can tap into for learning. Consider grammar-checking software. It is a form of machine learning software that ingests copious amounts of data (previous texts and the rules of English grammar) and checks your writing for errors. Does it make mistakes? Yes, since it may not recognize specific elements of style unique to your writing that skirt the rules of English grammar or that the context of a sentence calls for something a bit different than the norm. However, it is a useful bit of machine learning and one that we now take for granted in our word-processing programs.

Machine Learning in Accounting

Many accounting platforms have machine learning built into the system to help accountants and financial professionals do more with their data. A few machine learning examples from the world of finance and accounting include:

  • Forecasting: Machine learning programs can leverage both historic data as well as current market predictions to improve forecasting. Better forecasting offers companies smarter money management, for example, or better inventory management if they can forecast supply and demand with greater accuracy.
  • Fraud Detection: Manually reviewing accounts payable or receivable line by line is a thing of the past with new fraud detection tools. Because machine learning systems are good at pattern recognition, anything outside of an expected pattern can be brought to the user’s attention. These fraud detection features save many hours of tedious journal reviews and allow users to spot patterns with ease.
  • Risk Management: If the system has access to large data sets, it can review past data, identify patterns around known prior risks, and help detect similar risks in the future.
  • Compliance: Machine learning can augment accounting systems and provide notices, reminders, and more on key compliance issues and dates. The resulting reminders can help organizations remain compliant.

Can Machine Learning Take the Place of an Accountant?

Machine learning is, as we said, great at pattern detection. However, what to do once a pattern is detected requires the insights, skills, and experience of a professional accountant. No machine will ever replace a CFO or accountant. Instead, software that uses machine learning can help accountants complete tasks efficiently, improve predictive analytics, and prevent fraud.

Welter Consulting

Welter Consulting bridges people and technology together for effective solutions for nonprofit organizations. We offer software and services that can help you with your accounting needs. Please contact us for more information.