For many companies capturing lease accounting data will be the biggest implementation hurdle on the path to complying with the new FASB and IFRS standards. Few organizations have a centralized repository to track all of the information about their real estate and equipment leases. As a result, companies will need to go through a process to identify which data needs to be collected and where to find it. Once located the data will need to be abstracted from contracts, validated to ensure its completeness and reconciled between systems to confirm its accuracy. For each lease as many as 100 different pieces of data may need to be captured – the name and address of the leasing company; fixed and variable rent; frequency and timing of rent payments; options to renew, return or buyout the asset at End-of-Term. A recent PWC/CBRE study found that 73% of companies expected collecting data to be “somewhat difficult” or “very difficult.”
To help you with this massive undertaking, our team of leasing experts has assembled the ten critical success factors for capturing lease accounting data. The best practices are based upon our many years of working with Fortune 500 companies to transform and automate their lease accounting processes.
The 10 Critical Success Factors to Capturing Lease Accounting Data
1) Get Started Early
The SEC has defined implementation deadlines for the new lease accounting standards, which vary based upon your fiscal year and the private/public nature of your ownership. The earliest implementation deadlines for December 31st filers are for fiscal year 2019. However, the official deadlines don’t provide the full picture. The SEC is also requiring comparative reporting – three years of income statements and two years for balance sheets. As a result, you will likely need to start capturing lease accounting data well in advance of the official deadline. For some companies, as early as January 2017.
2) Get Expert Help
Although a data collection process might sound like a clerical process that should be delegated to the low-cost offshore resources, gathering the lease accounting information needed will require significant domain expertise. Interpreting complex contracts for real estate, technology, equipment and vehicle fleets can be quite complex. There are a finite number of experts in the market with the specialized knowledge of leasing business processes. And these experts will be in high demand. In the 12-18 months preceding the implementation deadlines we expect that there will be a shortage of talent in the marketplace.
3) Assign a Dedicated Team
We recommend staffing a dedicated team to manage the collection of your lease accounting team. Avoid the temptation to make it a secondary responsibility of a employees who have another full time job. The team should have one or more contract analysts. For example, you might have a contract analyst for real estate leases and another for IT and equipment leases. This team will liaison with various business units in different geographic regions to capture the necessary data for each lease.
4) Search External Systems
Don’t limit your search for lease accounting data to just internal systems. While your Accounts Payable, Procurement and Asset Management applications will be a great source of data, consider going to the true source as well – the lessor. Landlords, building owners, equipment manufacturers, commercial banks and independent lessors will have some of the most accurate, up-to-date records on leases. After all, they own the assets and their revenue generation efforts depend upon being able to regularly invoice for all their leases.
5) Collect the Same Data from Multiple Sources
We recommend that you attempt capturing lease accounting data from as many sources as practical – even if the data requests are redundant. Ask multiple different groups for the same information then compare what matches and what does not. Don’t be surprised if the asset owners in real estate, operations, IT or fleet management are collecting the same data as back office groups such as accounting, procurement and treasury, but in different ways. This approach will guarantee that the data is accurate as possible.
6) Consider a Staging Database
Before you start capturing lease accounting data, consider where you will house the information once you receive it. If you need to collect 100 different data elements for 5,000 different leases across your organization, you will have 500,000 different pieces of data.Will you upload this data directly into your new lease accounting application? Or will you house it in an interim “staging database” until you have guaranteed that it is accurate and up-to-date? The interim database could be simply a series of spreadsheets and a file system (to keep the contracts).
7) Define a Methodology for Fixing Data Errors
Once you have finished capturing lease accounting data, you will need to perform a quality assurance process before uploading it to your database. Expect that you will have missing data fields for some leases. For other leases you may not be able to find any data at all. And in other cases, the data provided by different sources does not match. To resolve these issues we recommend developing a methodology to fix the errors. Decide which is the most trustworthy source of data. Is it data from lessors? Accounts Payable? Asset Owners? Corroborate information between sources placing a higher value on data from the most trusted systems. As necessary, reach out to asset owners to confirm the accuracy.
8) Assign Ownership for the Data
Designate groups as being the owners of selected lease accounting data. Notify these organizations that they will need to periodically review the accuracy of the information such as the locations of IT, fleet and equipment assets; the likelihood of renewing, canceling or extending a particular lease; and the presence of any bundled service costs. This attestation process will occur not only during the initial data collection process, but on an on-going basis after you begin reporting using the new lease accounting standards. Capture all the attestations of data with a timestamp for audit purposes.
9) Define Post-Implementation Processes
Think beyond the initial data collection process to a longer-term, operational model. How will you ensure that the information in your lease accounting system is always accurate, complete and up-to-date. In addition to assigning ownership for the data (#8), you should also define automated workflows for change events. How will you notify accounting of changes to variable rents for real estate leases? Physical location changes for material handling equipment? Cost center changes for laptops and servers? Partial, mid-term buyouts of trucks and automobiles?
10) Automate Data Collection for New Leases
Another post-implementation issue to address is new leases. If your average lease term is four years, then 25% of your leases will come up for renewal each year. Some of those 25% will be canceled and replaced with another lease. The others will be renewed although key contractual elements such as rent and residual values will change. For each of these new leases, you will need to capture the raw data to ensure that your accounting is kept current. We recommend pushing your lessors to send electronic feeds of structured data for new leases. The data might be exchanged automatically via APIs or hand-keyed into a website. Either approach is more scalable and efficient than manually reviewing contracts.
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White Papers, Handbooks and Research Studies
Learn the differences between contract-level and asset-level lease accounting in this technical white paper. Review examples of the impact of asset-level decisions, judgments and events for material handling, data center and IT equipment.
Considering Lease Accounting Software to comply with the new FASB or IFRS standards? Download this eBook to understand the potential time and cost savings opportunities resulting from automation of lease classification and financial reporting.
The industry’s most comprehensive guide to collecting your lease accounting data. Follow our 10-step methodology to understand what data you need; where to find it; how to abstract it and how to clean it up. Over 50 pages of best practices and diagrams illustrate the process step by step.