# Infosys Whitepaper 
Title: Enabling QA through Anaplan Model testing 
Author: Infosys Limited 
Format: PDF 1.7 

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 WHITE PAPER  {{   img-description: a blue colored image of a large data room, in the style of systems art, richly layered, colorized, contrasting (floating left	) }} ENABLING QA THROUGH ANAPLAN  MODEL TESTING Abstract Anaplan is a cloud-based platform that can create various business  models to meet different organizational planning needs. However,  the test strategy for Anaplan varies depending on the application  platform, cross-track dependencies and the type of testing.  This white paper examines the key best-practices that will help  organizations benefit from seamless planning through successful  Anaplan testing.<|endoftext|>- Mangala Jagadish Rao - Harshada Nayan Tendulkar 

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  {{   img-description: business man and technology icons scribbled on paper, in the style of light indigo and indigo, printed matter, interactive experiences, polished concrete, high-angle, caffenol developing, website (fade in right background) }} External Document © 2018 Infosys Limited What is Anaplan?  Anaplan is a cloud-based operational  planning and business performance  platform that allows organizations to  analyze, model, plan, forecast, and report on  business performance. Once an enterprise  customer uploads data into Anaplan cloud,  business users can instantly organize and  analyze disparate sets of enterprise data  across different business areas such as  finance, human resources, sales, forecasting,  etc. The Anaplan platform provides users  with a familiar Excel-style functionality  that they can use to make data-driven  decisions, which otherwise would require a  data expert. Anaplan also includes modules  for workforce planning, quota planning,  commission calculation, project planning,  demand planning, budgeting, forecasting,  financial consolidation, and profitability  modelling.<|endoftext|>

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 External Document © 2018 Infosys Limited External Document © 2018 Infosys Limited 7 best-practices for efficient  Anaplan testing  1. Understand the domain As Anaplan is a platform used for  enterprise-level sales planning across  various business functions, its actual users  will be organizational-level planners who  have an in-depth understanding of their  domains. Thus, to certify the quality of the  Anaplan model, QA personnel must adopt  the perspective of end-users who may  Fig 2: Representation of Anaplan data integration  be heads of sales compensation or sales  operations departments, sales managers,  sales agents, etc.<|endoftext|>2. Track Anaplan data entry points  One of the features that makes Anaplan  a popular choice is its provision of a wide  range of in-built and third-party data  integration points, which can be used to  easily load disparate data sources into a  single model. For most business users,  data resides across many granular levels  and it cannot be handled reliably with  traditional Excel spreadsheets. Anaplan  offers a scalable option that replaces Excel  spreadsheets with a cloud-based platform  to extract, load and transform data at any  granular level from different complex  systems while ensuring data integrity.<|endoftext|>It is essential for QA teams to understand  the various up-stream systems from where  data gets extracted, transformed and  loaded into the Anaplan models. Such data  also needs to be checked for integrity.<|endoftext|>                                                                {{   img-description: a person in a dark white shirt uses their phone to see an article about a data center on a laptop, in the style of light sky-blue and gray, historical illustrations, datamosh, light green and gray, streamlined forms, uhd image, functionality emphasis  }}            

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 External Document © 2018 Infosys Limited 3. Ensure quality test data  management  The quality of test data is a deciding factor  for testing coverage and completeness.  Hence, the right combination of test data  for QA will optimize testing effort and  cost. Since Anaplan models cater to the  financial, sales, marketing, and forecasting  domains of an organization, it is essential  to verify the accuracy of the underlying  data. Failure to ensure this could result  in steep losses amounting to millions of  dollars for the organization. Thus, it is  recommended that the QA teams dedicate  a complete sprint/cycle to test the accuracy  of data being ingested by the models.<|endoftext|>The optimal test data management strategy  for testing data in an Anaplan model involves  two steps. These are:  • Reconciling data between the database  and data hub – Data from the source  database or data files that is received  from the business teams of upstream  production systems should be reconciled  with the data hub. This will ensure that  the data from the source is loaded  correctly into the hub. In cases of  hierarchical data, it is important to verify  that data is accurately rolled up and that  periodic refresh jobs are validated to  ensure that only the latest data is sent to  the hub according to the schedule.  • Loading correct data from the hub into  the model – Once the correct data is  loaded into the hub, testing moves on  to validate whether the correct data  is loaded from the hub to the actual  Anaplan model. This will ensure that  the right modules are referenced  from the hub in order to select the  right data set. It also helps validate  the formulas used on the hub data to  generate derived data. For every model  that is being tested, it is important  to first identify the core hierarchy list  that forms the crux of the model and  ensure that the data is validated across  every level of the hierarchy, in addition  to validating the roll-up of numbers  through the hierarchy or cascade  of numbers down the hierarchy as  needed.<|endoftext|>{{   img-description: people standing near computers with clouds outlined, in the style of commercial imagery, emphasis on the process, light teal and black, high-key lighting, uhd image, light orange and white (bottom)  }} External Document © 2018 Infosys Limited 

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 External Document © 2018 Infosys Limited 4. Validate the cornerstones  It is a good practice to optimize test  quality to cover cornerstone business  scenarios that may be missed earlier. Some  recommendations for testing Anaplan  models are listed below:  • Monitor the periodic data refresh  schedules for different list hierarchies  used in the model and validate that the  data is refreshed on time with the latest  production hierarchy  • As every model may have different user  roles with selective access to dashboards,  ensure that functional test cases with  the correctly configured user roles are  included. This upholds the security of  the model since some dashboards or  hierarchical data should be made visible  only to certain pre-defined user roles or  access levels • The Anaplan model involves many data  fields, some of which are derived from  others based on one or more business  conditions. Thus, it is advisable to include  test scenarios around conditions such as  testing warning messages that should  be displayed, or testing whether cells  that need to be conditionally formatted  based on user inputs that either pass or  fail the business conditions 5. Use automation tools   for faster validation  IT methodologies are evolving from  waterfall to agile to DevOps models,  leading to higher releases per year,  shorter implementation cycle times and  faster time-to-market. Thus, the test  strategy of QA teams too should evolve  from the waterfall model. Incorporating  automation in the test strategy helps keep  pace with shorter cycle times without  compromising on the test quality. Anaplan  implementation programs leverage  agile and possess a wide range of testing  requirements for data, integration and  end-to-end testing, thereby ensuring that  testing is completed on time.  However, there are times when it becomes  challenging to deliver maximum test  coverage within each sprint because  testing Anaplan involves testing each  scenario with multiple datasets. Thus, it is  useful to explore options for automating  Anaplan model testing to minimize delays  caused during sprint testing and ensure  timely test delivery. Some of these options  include using simple Excel-based formula  worksheets and Excel macros along with  open source automation tools such as  Selenium integrated with Jenkins. This  will help generate automated scripts that  can be run periodically to validate certain  functionalities in the Anaplan model for  multiple datasets. These options are further  explained below: Reusable Excel worksheets – This involves a  one-time activity to recreate the dashboard  forms into simple tables in Excel worksheets.  The data fields in Anaplan can be classified into  3 types: • Fields that require user input  • Fields where data is populated from  various data sources within Anaplan or  other systems  • Fields where data gets derived based on  defined calculation logic. Here, the formula  used