Best Practices for Data Loading into SAP ERP Systems

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1 Best Practices for Data Loading into SAP ERP Systems Summary An organization s ability to act swiftly and make business decisions is based on having access to complete and accurate views of enterprise data. Companies recognize the value in leveraging all of their corporate information and the benefits of reconciling data into consolidated views, but the path to get there can be difficult. Getting data into the company s ERP system in a timely and accurate manner is a critical success factor in business decisions. This white paper examines existing data-loading methods and best practices to easily incorporate data into SAP solutions. A white paper by: Winshuttle, Inc. Bothell, WA 98012, USA

2 Introduction It is a core business principle that to run a successful company, assets must be managed effectively. However, there is an often overlooked asset that, if correctly harnessed, is a turning point in competitive advantage, particularly with the increasing sophistication of enterprise wide business management systems such as SAP ERP. This asset is the core data produced in abundance by every company in the world. Corporate data sets include transactional data and master data. DATA MIGRATION DATA MAINTENANCE DATA INTEGRATION DATA CREATION Fig. 1 - Data loading use cases Managing large amounts of data can be a significant challenge to most organizations. Some of the common data management tasks include: Data migration: loading legacy systems data into SAP applications during initial SAP implementation or M&A activity Data maintenance: mass changes to SAP data for price changes and payroll changes Data integration: loading vendor invoices or bank statements into SAP applications Mass data creation: creating new master data (materials, vendors, customers, etc.) or transactional data (journal vouchers, invoices, etc) in SAP systems A common theme among these data management applications is data loading loading of data into SAP systems from external files such as spreadsheets or other databases. The limited resources in IT and in the lines of business struggle to complete these data-related tasks in a timely and accurate manner. However, if the best practices described in this white paper are followed in each stage of a data loading process, these challenges can be overcome Planning the data load project Developing templates and preparing the data Running the data load process Post data load activities PLANNING DEVELOPING RUNNING POST DATA LOAD 1. Planning the Data Load Project Fig. 2 - Stages of a data loading project Every data loading project should have a plan that includes quality and user acceptance as the top priorities. Preparation is key to the success of any operation, and data loading is no exception. Items to be considered when planning a data loading project: Selecting the right tool for the job For small projects affecting fewer than 50 transactions, manual data entry may be the best choice. However, when uploading large amounts of data, such as employee records, pricing conditions, material masters, purchase orders, or customer invoices, manually keying in the data is resource-intensive, time-consuming and stressful for data entry personnel and IT support teams. In addition, the manual entry of data increases the risk of errors, thereby increasing the total cost of ownership (TCO) of SAP solutions. - Custom programming One alternative to the manual entry of data into an SAP system is to write custom ABAP programs. Many companies have developed custom programs for very large data loading tasks that will remain static. These programs can streamline the repetitive entry of hundreds of thousands to millions of records. However, creating robust programs involves multiple iterations of requirements gathering, programming, testing, documentation, transporting and refinement, and these programs may be used only once or twice a year, making the effort particularly costly in terms of man hours and ROI. Using a program that was hastily put together or one that has not been well-tested can damage or destroy data. 2

3 - SAP-provided tools If technical resources are not limited, one approach to create and change master and transactional data is to use the data importing tools already resident in SAP applications such as BDC and LSMW. LSMW can be a very effective way of creating data in a new SAP implementation. However, SAP technical tools are intended to be used by technical resources in IT departments, rather than everyday business users. In addition, any data import scripts and programs added to the SAP system need to be maintained as SAP versions are upgraded even if they were created as one-time-use tools. Finally, your business users require extra authorizations to perform uploads using SAP-provided tools. SAP-certified third-party tools Third-party tools such as Winshuttle s transactionshuttle do not reside inside the SAP system, so they generally do not require extra authorizations and can be used by everyday business users. transactionshuttle simplifies the data loading process because it does not require any programming and does not require any technical resources. For your SAP systems, data loading using a third-party tool is exactly the same as manually entering data, only at a much faster speed. Uploading to SAP via the correct interface Data should never be uploaded directly to SAP tables. Writing directly to SAP tables circumvents the data validation provided by normal SAP transactions. Always upload data via pre-configured SAP transactions, BAPIs or IDocs, and use tools such as BDC, CATT, LSMW or a qualified third-party tool. This maintains the validations configured in each transaction. Ensuring regulatory compliance One of the most common SOX audit concerns is that users in IT departments have very broad access to production data in SAP systems. Data uploads should be carried out by data owners who are authorized to perform them. Check to be sure that rights and duties are assigned to different individuals separately so that no one individual has the power to divert business or transactions in a fraudulent manner. Sharing templates There is no need to re-invent the wheel for each transaction. Reuse templates developed for previous uploads and share them among departments. Keeping a repository of templates, in SharePoint or a shared file repository, along with a common naming convention, will enable users to easily find a previously created template. Planning for iterations Due to changes in requirements and errors in data, data loading projects are iterative in nature. Plan to create several scripts and allot time for iterations. 2. Developing Templates and Preparing the Data The following best practices should be considered while developing the data loading scripts and templates: Develop and test on non-production systems Testing data loading templates thoroughly on a non-production system allows you to detect and correct systematic errors before moving the data into production. Use a peer-review process To verify their accuracy and performance, any scripts or templates developed should go through a peer-review process. This process can range from a very simple method of looking over one s shoulder to a complete workflow-based review process. Use a versioning method to keep track of changes Since data loading scripts tend to change as requirements change, use a version control system to keep track of these changes. All document management and collaboration systems, such as Documentum or SharePoint, offer easy-to-use version control features. 3

4 Develop data validation methods in conjunction with basic load scripts Validating data prior to loading it into the SAP system is good way to avoid getting and reprocessing errors during the loading. Data can be validated in two ways: 1) Using Excel references and dropdowns, simple validation rules can be built into the Excel data file itself so that invalid data is not created in Excel. 2) Building simple validation scripts which simulate entering the data into required SAP fields, but do not post or save the data. Create an Excel template with an embedded loading script A data loading script is usually associated with an Excel file format since Excel fields are typically mapped to SAP fields within the data loading script. It is significantly easier to manage a single file than two linked files; therefore, embed the script within the Excel file template so that only one file needs to be managed. The following best practices should be considered while preparing the data files to load: Keep the data in native format Minimize the number of transformations that the data has to go through. The Excel files that you need to load into your SAP system may need to undergo some format conversions or field manipulations before the loading program will accept these files. Some data loading programs will require a CSV format or a tab-delimited format, requiring you to transform the native Excel file into a CSV file before every run. Ideally, your data loading program should allow you to work with your native Excel file format. This will avoid the extra conversion steps and will also allow you to use Excel formulas, such as VLOOKUP and Excel formatting directly. Use data cleansing tools To avoid loading poor quality data into SAP systems, use data cleansing tools to remove duplicate records, fill in missing values, etc. Excel 2007 includes some data quality tools such as duplicate detection, and several other third-party data cleansing tools, such as Trillium and Data Flux, are available in the market. Use a data review process To verify the accuracy of the data prior to loading it, the prepared data files should go through a peer-review process. As before, this process can range from looking over one s shoulder to a complete workflow-based review process. 3. Running the Data Load Process When running data loading scripts, consider these best practices: Data ownership and login credentials Make sure that the data loading is carried out by users who own the data and who login using their own SAP credentials. This ensures regulatory compliance and keeps the correct audit trails in the SAP system. This also makes sure that the data goes through the correct validation rules before being posted into the SAP system. Additionally, empowering business users to do the upload themselves, using SAP tools or third-party tools, saves time and money in data loading projects and frees up IT resources. Error handling Any data loading project is sure to have records that will not be accepted by SAP applications due to errors, so it is important to make sure you are prepared to process them. Ideally, the data loading tool you use will show you the SAP error messages alongside the data records. This will make it easy to identify the cause of those errors, allowing you to correct them in the data file and reload only the error records. If you cannot identify the causes of the errors, the recommended method is to process those records in a foreground (step-by-step) mode. 4

5 Log each run separately Since you may have to run a single data file multiple times while processing the errors, it is recommended that you log each run separately. Either keep a copy of the intermediate run files or log the results of each run in a separate column. Prevent double posting of transactions Another risk of multiple runs through a data file is that some transactional data may end up being posted twice into the SAP system. Make sure you prevent such double postings by keeping track of the successfully posted records separately, or by ensuring that your data loading tool prevents double posting. Avoid data loads during high demand, peak-business hours Some data loads, especially changes to master data, may affect other users who are working on the system. Also, a large upload may affect the SAP system performance. Your data loading tool should provide a scheduling feature that will allow you to schedule large uploads during off-peak hours. Develop a process to backup old data When a data loading script is intended to change existing data in your SAP system, make a backup of the old data before effecting the change. A simple way to backup data is to read the current values of the fields that you are trying to change in your SAP system and save that into a file. Having this will allow you to revert to the original data in case of problems with the data loading script. 4. Post Data Load Activities The following best practices should be considered after completing a successful data load run: Archive the data file and the associated scripts After a data file has been successfully processed, archive that file showing the log messages into your document management system. This will ensure complete traceability of data for regulatory compliance purposes. Share templates The data loading scripts and templates that you have developed should be kept in a common repository so that they can be shared with other users within your organization. Conclusion Applying the best practices discussed in this white paper will ensure quicker, error-free and compliant data loading, regardless of whether the data sets are large or small, or whether the data is master or transactional data. Training business users to apply good processes and enabling them with the right tools to upload data improves the decisions that a company makes by guaranteeing their data is up to date. This improved accuracy can be a huge competitive advantage, and when combined with the operational flexibility that users have with the right tools and practices, can be instrumental in creating revenue growth. Winshuttle, Inc. is the leading provider of data entry and data download tools for SAP users worldwide. Winshuttle s products replace manual data entry and complex technical tools by easily and securely shuttling data between Microsoft Excel and SAP solutions. Winshuttle s flagship product, transactionshuttle, effectively bridges the needs of business users with the governance requirements of IT. transactionshuttle transforms business processes for both implementation and post production projects, including data import, data quality and data integration. Managing SAP data has never been simpler for the hundreds of Global 2000 companies that rely on Winshuttle. Headquartered in Bothell, Washington, Winshuttle has offices in the United Kingdom, France and India. For more information visit info@winshuttle.com or call Corporate Headquarters Bothell Everett Hwy Suite 110, Bothell, WA Tel + 1 (800) Fax +1 (425) United Kingdom 64 Kimber Road, Southfields, London, SW18 4PP, U.K. Tel +44 (0) Fax +44 (0) France 58, rue Delalain Maisons-Alfort Tel +33 (0) Fax +33 (0) India Third Floor, Tower D DLF Building, Technology Park Chandigarh , India 5