The importance of Financial Analytics
SupportAbility has been working with Service Providers operating under the NDIS since the beginning of the NDIS trial sites in 2013. The great majority of organisations operating under NDIS experience rapid and significant growth. This growth places considerable strain on the organisation's financial resources which subsequently require a much higher level of strategic financial planning and management. The cash-flow pressures stemming from growth are exacerbated by working under the NDIS' claiming in arrears model, and also the fact that the pricing levels set for NDIS Support Items in the Price Guides mean that support profitability varies greatly, and some supports will almost certainly guarantee a loss.
The Board of Directors and/or Executive Management team for an organisation are charged with the responsibility of its financial stewardship. They will need to make expedited decisions based on comprehensive financial information, and will likely ask the organisation's Finance team to generate reports that provide insight into the organisation's financial data from different angles. They may also want to compare the profitability of specific Services and Sites for example, or from other perspectives.
Analysing financial information from different perspectives allows an organisation to identify issues around profitability with a fine focus lens. To steward an organisation through these cash-flow pressures, the Board and Executive Management will require more insight and detail than ever before. Therefore it is crucial that organisations develop good financial strategies and systems to facilitate this level of detailed enquiry.
Categorising Financial Data
Why is the categorisation of financial data important?
SupportAbility is designed to export invoice data across to your organisation's finance system. An organisation's finance system will be responsible for distributing those invoices and managing the accounts receivable process.
In order to look at revenue from different perspectives, revenue data needs to be categorised in specific ways. For example, let's assume that SupportAbility is sending an invoice across to the finance system and that this invoice contains one support item for 3 hours of group-based community support on a Wednesday. This support was provided under the Learn to Swim Program offered by the Community Options Service at the Melbourne Site. The client paid for this support using their NDIS funding package. With this information, the revenue could be potentially codified using one or more of the following categorisations:
- Site: Melbourne
- Service: Community Options
- Program: Learn To Swim
- Day: Weekday or Wednesday (depending on the level of detail you require)
- Payment Method: NDIS
Categorising revenue in this manner allows an organisation to investigate this information from a number of perspectives. This categorised revenue information from SupportAbility, when paired with the expense information already contained within the finance system, helps organisations identify profitability issues.
Based on the above categorisation, reports could be generated to identify the profitability of the Melbourne Learn to Swim program on a Weekday versus a Saturday for example. Or the profitability of Services delivered under Fee for Service (user pay), versus those delivered under NDIS.
Available tools for categorising financial data
Most finance systems have two primary tools for categorising financial data, both with distinct purposes:
- Chart of Accounts (General Ledger Codes):
The Chart of Accounts is the list of account (categories) that a Finance system uses to group revenue and expenses for reporting purposes.
- Revenue accounts may be structured to group revenue by Service type, Site and/or Funding Type i.e. Payment Method.
- Expense accounts are often used to group related expenses such as wages, and to also separate them from other expenses such as utilities.
These accounts categorise revenue and expenses for the purposes of reporting via the Profit and Loss statement. Please review the General Ledger Codes article for more information and examples of how this can be set up in SupportAbility.
- Jobs (Job Codes):
Jobs are a tool for categorising revenue and expenses on a more detailed level for the purposes of business intelligence and financial analytics.
Selected finance systems include financial analytics tools, whereas others such as MYOB require third-party business intelligence tools such as Calxa to be used for this purpose.
The Job Coding methodology available in SupportAbility allows each instance of revenue to be linked to multiple categories (such as Site, Service, Program, etc.) for the purposes of reporting and analytics.
Please review the Job Codes article for more information regarding which Job Code Components are available for set up by SupportAbility, for your organisation to then configure as required.
The difference between General Ledger Codes and Job Codes
- Client Funding GL Codes: are codes with the ability to reference multiple entities, including the Site and Service being invoiced, as well as the Funding Type the Client used to pay for the Activity e.g. NDIS.
Different GL Code taxonomies can be employed to provide either a singular individual reference e.g. Site (ACC-MELB) or a combined reference to two or three entities e.g. Site, Service and Funding Type (ACC-MELB-DAY-NDIS).
- Job Code Components: are specific and isolated to the reference entity they relate to, such as Site, Service or Program for example. Unlike GL Codes, Job Code Components cannot provide reference to more than one entity. This is why separate fields are available for the each Job Code Component.
To illustrate this point, a Service Job Code Component will only ever reference the Service of the Activity being invoiced. Whereas the GL Code, could potentially be configured (using the Site, Service and Funding Type taxonomy) to provide a combined reference to the Site and Service of the Activity, as well as the Funding Type the Client used to pay for the Activity in a single code.
Deciding how to categorise financial data for your organisation
When integrating SupportAbility with an organisation's finance system, the first instinct is often to make SupportAbility work with the existing Chart of Accounts and job codes structure that the organisation utilises. However, it is recommended that Service Providers treat the introduction of SupportAbility as an opportunity to review the current structures and then plan and implement a more strategic approach to get the most out of this functionality.
Before finance integration begins and the Chart of Accounts (General Ledger Codes) and Job Code structures are finalised and configured in SupportAbility, it is recommended that providers consult with their Board of directors and/or Executive Management team, to discuss the options available and develop a strategy based on the information they may require now and in the future.
Financial analytics and business intelligence tools such as Calxa should also be investigated prior to Finance & NDIS integration, as the requirements & capacity of these tools will influence how your organisation will design a strategic job coding taxonomy for example.
SupportAbility provides various options that allow Providers to categorise revenue data in a more detailed manner for analytical purposes. The integration between SupportAbility and an organisation's Finance system is the perfect opportunity to review the organisation's current way of categorising revenue data strategically and ensure that it is structured in a way that will serve the organisation in the future and assist the Board & Executive Management navigate the cash-flow pressures associated with the NDIS.
Most providers use a simplistic and consistently structured Chart of Accounts (General Ledger Codes) to meet the Profit and Loss statement requirements, and a more strategic and possibly more detailed Job Code structure to allow the financial data to be analysed from different perspectives.
CAUTION: it is important not to use too many categorisation types when deciding on a Job Coding taxonomy, as creating unique Job Codes for every possible combination of Site, Service, Day of the Week, Program and Funding Type, for example, is generally too difficult to manage in most finance systems and the overhead costs would quickly outweigh any benefit that the detailed information would provide.
Deciding which methods to utilise for categorising financial data is an important strategic decision for organisations operating in the NDIS. It is recommended that organisations take the opportunity to review their financial analytics tools and existing structure prior to financial integration with SupportAbility.