How to organize the planning process in the SAP Analytics Cloud

Planning and budgeting systems have existed for decades, and one of the main problems of this class of systems is still insufficient flexibility. Almost everyone is coping with the time-consuming task of recalculating and consolidating data. And when it comes to changing the business model and the data model, according to which the recalculation of planned indicators takes place, almost no one can cope. For example, when carrying out reorganizations or deciding on the outsourcing of individual production processes, the planning system should adapt and allow for very quick changes to all settlement documents related to the formation of cost and financial results. Consideration of these requirements should not lead to the formation of a system in which planning costs will exceed the effect obtained from the implementation.

Planning is the setting of strategic goals of a business, and then determining how to achieve them by creating annual budgets, tracking progress in forecasts and modeling scenarios to find new opportunities. All plans are formed by projecting historical data for the future, collecting information from various functional areas and taking into account trends, risks and potential market opportunities. For example, the executive management of a bicycle manufacturer notes a growing demand for electric bikes and decides to increase sales of this type of product by 20% over the next three years. In the budget for next year, the finance department determines the total costs and revenues resulting from the implementation of this plan.

However, activity planning is not limited to executives and financial analysts. There is a collaboration of departments throughout the organization:

• Sales managers set new quotas and determine which regions and to what extent will increase sales. They drive sales of e-bikes with higher commissions.
• The marketing department is planning promotions and campaigns to increase e-bike sales.
• The operations department ensures the availability of the supply chain and production capacity to increase inventory for this type of product.
• The human resources department plans to hire technical specialists who have experience working with electric motors and create new training resources for existing staff.

Each of these actions is associated with a central financial plan and a common goal set by management. Since any plan is complex and is formed with the participation of all departments of the company, working with stand-alone spreadsheets or in scattered planning systems can slow down the process, introduce errors and uncertainties. It also makes it difficult to adapt to a rapidly changing market.

In this situation, the SAP Analytics Cloud helps a lot due to the wide range of planning, business intelligence, forecasting and collaboration functions that make the planning process easier and faster. The simplicity and speed in this tool is due to its flexibility. At each stage, changes can be made, and the next and previous stages will reflect the changes made.

In general, the planning process in the SAP Analytics Cloud looks like this (Fig. 1)


Figure 1.

Prepare. First, we prepare the data for work: we connect to the sources, create a planning model based on them. Subsequently, it will be automatically enriched with new data from source sources in accordance with a schedule specially configured by us.

Schedule Next, the process of forming a calendar of tasks takes place, which allows you to organize many parallel workflows, appoint executors and reviewers, and set deadlines. The calendar tracks the progress of tasks and processes and the workload of employees (Fig. 2).


Figure 2.

Predict.Of course, when drawing up a plan, historical data, or a forecast based on them, always always forms the basis. Using the predictive forecasting function, at the click of a button, you can get an automatic forecast and display it on the graph of the time series dynamics or put it directly in the main table with the plan (Fig. 3).


Figure 3.

Plan. Next, we go directly to planning. Using these features in the SAP Analytics Cloud, you can implement:

• Building strategic plans.
• Budget analysis and distribution of its articles.
• Comparison of budget and forecast with fact.

One of the biggest planning problems in an organization is the need to build many plans: sales, production, finance and HR. And a separate issue is the creation on their basis of one consolidated.

For example, when an analyst completes sales planning, he can transfer the generated revenue to P&L planning. Similarly, HR and sales, sales and finance plans are linked. At the same time, financial data directly come from SAP S / 4HANA, HR data from SAP SuccessFactors, and sales data from SAP IBP (Fig. 4).


Figure 4.

For example, we need to update the sales forecast for a certain type of product. To do this, we simply select the desired cell and enter the desired percentage of growth. After making changes, the system will recalculate all the dependent indicators and highlight them in color. In addition, the tables in the SAP Analytics Cloud can work as Excel sheets, that is, we can freely do some intermediate calculations right on the report page (Fig. 5).


Figure 5.

The tool also allows you to automate allocation processes.

Distribute Using this function, the user can move values ​​from one cell to another at the same hierarchy level within any available dimension. Suppose we want to redistribute planned values ​​of operational costs between categories of goods (Fig. 6).


Figure 6.

After selecting the desired source cell and calling the "Distribute" function, a dialog box appears that allows you to simulate various options for distributing the existing value. We can choose the analytics and the necessary hierarchy level within which values ​​can be moved. In the example above, 50 million are redistributed from the Apparel product category to Footwear.

Spreading Using this function, you can implement the process of distributing values ​​from a cell at the top of the hierarchy to the bottom. This can be done automatically or by customization.

If a new value is entered into an empty cell, then for the lower levels of the hierarchy of the same dimension, this value is distributed in all articles in equal shares.

But there is also the opportunity to make the distribution manually. For example, we want to distribute the cost of wages by region. After selecting the desired cell and calling the Spreading function, we see a dialog box. In it, you can specify the desired distribution of this type of cost manually, use the copy function from any selected cell in the table, or select one of the available autofill scripts (Fig. 7).


Figure 7.

Assign.Another allocation function allows you to distribute the value across several cells at a certain level in the hierarchy of any analytics. Unlike the Distribute and Spreading functions, a specific source cell is not required here. Suppose we want to add 50 million to the cost plan for sales and marketing for a particular type of product. Using the Assign function, we can add a value to a specific cost item and distribute it (Fig. 8).


Figure 8

The tool also allows you to automate the planning workflow by creating Data Actions. These are processes that include copy and paste functions, as well as complex formulas using scripts. With their help, it is possible to simulate processes such as cash flow planning, depreciation, and transfer operations. Processes of different difficulty levels are developed by the user in a convenient simulation mode, can be built into reporting and launched at the click of a button. In other words, it is an analog of macros in Excel, but it works in low code mode.

Copy operations make it easy to move data between different models. For example, if we have separate models for planning headcount and expenses, we can use Data Actions to copy data from these models to the central financial model.

Suppose we want to create an automated process for transferring balance values ​​to the end of the previous period in a cell from the balance to the beginning of the current one (Fig. 9).


Figure 9. You can

build such a process using a simple visual editor or by writing a script in the BPC logic language, which may be familiar to SAP BPC consultants. It is important to note here that the system helps the user build code by offering possible options for functions.

This is the process built in the visual editor (Fig. 10).


Figure 10.

Creating a Data Action takes place in several stages. First we “draw” the content structure:

• first of all, we impose conditions for the transfer of only assets and liabilities accounts and equity,
• then we model the formula for transferring the closing balance of the previous month to the opening balance of the current month,
• the second formula will contain the calculation of the closing balance of the current month,
• we place all the formulas in a cycle so that the actions that we have prescribed will be repeated for each month of the current year (Fig. 11).

Figure 11.

After constructing the content structure, we select a specific data slice, apply filters and begin to fill the formulas with the context: with specific measurement elements and indicators, in other words, we explain to the system exactly what the given formulas need to be applied to.

Then we add the button that launches the created Data Action directly to the analytical report, and we get the necessary results when it is clicked (Fig. 12).


Figure 12.

Data blocking. This functionality will allow you to impose restrictions on the editing of certain data sections for specific users or their groups. If further changes to the data blocking settings are required, you can schedule them in the task calendar, which was mentioned at the beginning of the article (Fig. 13).


Figure 13.

Versioning. In addition, the user is able to see how the various plans relate to each other and to the actual data. An analysis of deviations should be made and plans should be kept within budget. All this is possible due to versioning, which allows you to simultaneously build alternative planning scenarios and share them within the system, without creating confusion and keeping it unchanged (Fig. 14). original dataset.


Figure 14.

Visualization.The final stage of the planning process in the SAP Analytics Cloud will be the reflection of the results in a way that is convenient for visual perception. For each version of budgets and forecasts, visualization objects can be built that clearly reflect the difference between them (Fig. 15).


Figure 15.

Communications. In addition to all these stages, the entire planning process is accompanied by constant communication between users of the system. Employees can leave comments on each schedule or a specific cell of the table, mark any user of the system and conduct a discussion in a special chat (Fig. 16 a, b).


Figure 16 a.


Figure 16 b.

Thus, the planning methodology in the SAP Analytics Cloud is a cycle that allows you to put all the processes “on stream”, while leaving the possibility of flexible changes.

SAP Analytics Cloud is suitable for building a corporate planning system for the company, as well as for point plans of individual departments.

This tool is a stand-alone solution and can become part of a multi-vendor architecture. The integration of SAP Analytics Cloud with SAP solutions is native, in addition, there is standard business content for various industries and lines of business. Many of the predefined reports from this list include planning scenarios for tools such as S / 4HANA, IBP, Ariba, Success Factors, and many other SAP solutions. We'll talk about joint planning scenarios with SAP Analytics Cloud in the following articles.

In addition, in the next article we’ll talk about AutoML and its capabilities, as well as how to use the SAP Cloud Platform to create extensibility for ERP-systems.

Posted by Anastasia Nikolaevich, SAP CIS Business Solutions Architect