@Tiffany.Rice @ChrisWeiss @Beauram The topic of COE's being the drivers of their organization's connected planning journey is a really interesting one. In my experience I don't often see the backlog "dry up" after a few models are in production - it is often the opposite. If the value of these models can be demonstrated across the organization, new business units and functional areas will start lining up at the opportunity to get into Anaplan. At that point it often becomes a prioritization effort in which many important factors need to be considered. At Cervello we think about this prioritization effort in two phases. The first is a scoring exercise in which all potential use cases are scored against a series of measures (e.g. business impact, data readiness, etc). This exercise will help segregate the near-term use cases from the mid-term and long-term use cases. From there, creating the time-phased road map is dependent on additional factors such as key planning milestones and process dependencies.
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As more organizations embrace Anaplan as their cloud-based platform for business planning, many are looking to establish an internal Anaplan Center of Excellence to support their growing footprint. However, establishing a Center of Excellence can feel like a daunting task with no clear steps on how to get started. Although there are many areas to consider when establishing a Center of Excellence this article focuses on one area that every Center of Excellence should include: a model building standards document.
A model building standards document is your internal knowledge repository for all things Anaplan. This centralized guide can play a very important role in your long-term success with using Anaplan. A carefully constructed document can provide a wealth of benefits, including the following:
An intuitive and consistent model design to make life easy for model builders and accelerate learning for future model builders
A user-friendly experience for end users, maintaining familiarity across models
Certainty that all of your models are designed with the latest best practices
Assurance that only well-tested development work is present in your production environments
Confidence that you are unlocking the full potential of Connected Planning across models
As you develop your own model building standards document, here are seven components to consider:
Model Layout and Naming Conventions
A set of guidelines for model layout and naming conventions is a model builder’s best friend. Introducing standard-naming conventions for factors such as actions, processes, modules, and line items is an easy way to ease the burden on a Center of Excellence that is responsible for maintaining several Anaplan models. These standards help model builders easily transition from one model to the next and allow new resources to quickly get ramped up across multiple models. Whether you are using the conventions outlined in the Planual or have your own set of standards, proper documentation is essential.
A robust model design is the first step toward any successful Anaplan model build. When you are introducing new models into your Anaplan environment, a carefully assembled list of design principles can be a great accelerator to the design process. The 10 guidelines for pioneering model builders offers a great start to this list, but over time, you will be able to expand your list. Documenting these principles will provide an added level of quality assurance for each new model in your landscape.
Front-End Dashboard Design
When it comes to the long-term success of your Anaplan footprint, a user-friendly experience is as important as the model design. Being consistent in your dashboard design and routinely incorporating best practices is the easiest way to keep your end users happy and your adoption rates high. While it is relatively easy to develop an Anaplan dashboard, keeping a few basic tenants in mind can go a long way toward creating intuitive—and beautiful—dashboards for your users. A key responsibility of your Center of Excellence is ensuring that your model builders are delivering high-quality dashboards that will help your users enjoy their time in Anaplan. Defining and properly documenting these tenants will help all of the model builders within your Centers of Excellence follow a consistent approach.
Application Life-Cycle Management
When you have Anaplan models deployed in production, a robust Application Lifecycle Management (ALM) process will help ensure that all development being released into production has been properly tested. If you are not using ALM, consider introducing it into your Anaplan landscape. However, using the ALM functionality on its own will not be enough. Only when you introduce a carefully defined governance process will you realize all of the benefits that Anaplan’s ALM functionality has to offer. This process should be outlined in your standards document to ensure that all future models follow a standardized approach to ALM.
Data Hub Governance
If you are using Anaplan, you probably already have a data hub model in place. As your Anaplan footprint grows, you will likely add more data sources to your hub. Additionally, some landscapes require more than one hub to store sensitive data, such as employee salaries. There are some cases in which data can be loaded directly to a model and others where it should almost certainly be routed through a data hub. As such, it is important to define a set of guidelines for when data should be flowed through a data hub and how it can be stored most effectively.
Integrations and Scheduling
Defining best practices for moving data between models will allow you to get the most value out of your Connected Planning architecture. What integration tools are you using to move data from your data hub into your models? Which models talk to each other? What is your process for setting up new connections between models? Having a process outlined in your document will allow you to quickly set up powerful new connections when new models are brought on board.
Although Anaplan offers reporting functionality, don’t assume that it will be the solution for all reporting requirements associated with the planning process, especially if you already have access to other point solutions for reporting. Defining which types of reports are best suited for Anaplan and including this list in your document is a great first step toward developing a strong point of view about your reporting strategy.
Creating a model building standards document is a great way to jump-start your Center of Excellence's capabilities. However, to serve you most effectively, it should be a living, breathing document. As new functionality is released and as your team continues to learn, the document should be continually revamped and revised. A well-maintained document provides a layer of standardization and governance that will help ensure you are getting the most out of Anaplan as your footprint grows.
Cervello, a Kearney company, is a Global Strategic Anaplan Partner that helps smart businesses win with data. We optimize business performance, improve business analytics, and solve complex data challenges. We specialize in designing connected planning processes and analytics using transformative cloud-based technologies to maximize business value and provide deep insights into business performance. We work with enterprise clients in the functional areas of Finance, Operations, IT, and Sales & Marketing. Visit mycervello.com for more information.
This article was written by Cervello in conjunction with Anaplan and the Centers of Excellence team.
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During the holiday season, the ability to analyze and react to data effectively can be the deciding factor between having your shelves stocked or scrambling with inventory transfer issues. Historic data can provide the basis for true statistical forecasting, accounting for seasonality, and other retail trends. Cleansing the data will provide a consistent baseline and serve as a foundation for analysis, which can be presented using best-in-class dashboards to empower your business. Using Anaplan, retailers now can sense trends and pivot accordingly to make the holidays as successful as possible!
“The earliest GPS was essentially a digital map that led drivers through a predetermined route faster and with greater ease than a paper map. But as early GPS could not account for traffic jams, road hazards, or other variables, it did not warn drivers to pivot or course-correct to account for the unplanned. Similarly, many companies are currently making major investments in digitizing and automating their supply chains to make them better informed, more frictionless, more cost-efficient, and hence more capable.” Excerpted from “Why Supply Chains Must Pivot,” MIT Sloan Management Review.
In some ways, holidays are the most reliable times of the year. They take place the same time every year, they are focused on the same type of celebration—whether it be mothers, fathers, seasons or moon cycles—and they involve the same groups of people. Conversely, they are the definition of chaos for most retailers when it comes to the forecasting process. In the period leading up to a holiday, supply chain demand can increase exponentially, creating broad shifts in timetables and priorities.
The ability to sense and pivot to meet changes in demand is critical. By using historical data and a robust statistical forecasting model, Anaplan can help transform the holidays into something to look forward to for retailers.
Here's a look at how a multinational beauty company leveraged Anaplan and data best practices to optimize the supply chain forecast across more than 3,000 retail outlets.
How Did Last Year's Data Impact This Year's Decision?
The company had a wealth of prior holiday data, but its challenge was to mine that data for insights on how to adjust its supply chain to achieve a sustainable advantage for the coming year. To create a global forecast that was both accurate and valuable, we used a statistical forecasting model built in Anaplan to forecast key Mother’s Day SKUs across more than 3,000 stores.
The model analyzed the data and applied 30 statistical forecasting methods to identify the best-fit method that would produce the most accurate forecast. Because the Mother’s Day SKU data set was very seasonal, methods that performed better with seasonality—such as additive and multiplicative decomposition—were often identified as the best fit based on error percentage.
Once the demand forecast was produced, an inventory deployment model was constructed to integrate with the demand forecast. The inventory deployment model used the demand forecast—along with safety stock and cycle stock calculations—to identify a right-sized inventory for each store based on the remaining demand. The model then used supply chain assumptions, such as lead times from distribution centers to stores and minimum order quantities, to create inventory deployment recommendations in support of the right-sized inventory value.
As part of this initiative, we conducted a study to understand the financial impact of using the inventory deployment recommendations from Anaplan, as opposed to the actual purchase orders that were submitted by the company’s retail outlets. The study estimated that the Anaplan-generated inventory deployment recommendations offered an opportunity to improve net revenue by between 7 percent and 16 percent based on a reduction of stock-outs and excess inventory levels.
More About Connected Planning:
The Truth About Sparsity: Part 1
The State of Connected Planning Trends Review
Sales Planning Meets Production Planning
The Importance of Clean Data
All retailers have data and most have too much of it. Having data that is clean and mapped correctly can facilitate a smoother forecasting process. This can provide the clarity and normalcy needed to get through the sometimes-volatile holiday season.
For new SKUs with no history, we used Anaplan to create a mapping to similar SKUs to construct a data set on which a forecast could be built. This allowed us to accurately build out a fully loaded forecast utilizing all the SKUs available. In addition to utilizing SKU mapping, we used Anaplan to normalize lost sales due to stock-outs to create a more reliable data set.
The Benefits of Building Forecasting Dashboards
To harness the power, flexibility, and scalability of Anaplan, we created a set of dashboards using the new user interface. The dashboards provided key insights that allowed our client to easily understand the recommended shipment allocations and supporting data, as well as how the current season was trending weekly compared to previous years' sales metrics. These insights gave them the ability to sense in-store demand more accurately and pivot their replenishment orders accordingly.
Data is Your Saving Grace
Like most holidays, the past can be a blessing and a curse. Having historic data in your model can provide your organization with the ability to sense and pivot to accommodate increased demand and address inventory issues. Normalizing your data to create a consistent foundation and using Anaplan’s statistical models to accurately analyze your data, can provide your organization the competitive advantage needed to survive the upcoming holidays.
What are some other methods you use to make your seasonal forecast more insightful? Leave a tip below and let’s discuss it!
Brian Gallagher is a Manager and Anaplan Solution Architect at Cervello responsible for helping clients design & deliver Anaplan models. He is also a business process subject matter expert with experience re-designing processes based on industry standards.
Brian has over eight years of finance & technology experience, the last four of which have been focused on process re-design & delivering Anaplan solutions. He has served as the implementation lead on multiple enterprise-level clients. Brian earned a B.S. in Finance from Fairfield University with a minor in Mathematics. He has also earned his MBA from the University of Massachusetts.
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