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SAP Analytics Cloud, Scenario and What-If Analysis​

 

Self-Service Scenario and What-If Analysis​

In these uncertain times it is clear analyzing different scenarios of What-If something would happen in the future has become more relevant. We see more business users asking and finding answers to these questions thru data. Therefore, scenario analysis has become an important topic in the agenda of business intelligence leaders. However, many lack the needed technology and skills to provide such guidance in an easy to consume and understandable way.

With the SAC QRC4 release we are releasing the capability of what-if analysis in stories to support the business analyst and information workers to combine data visualizations and storytelling.  However, in an uncertain business climate it may not be enough to just simulate on historical data, but users need to create their agile data-driven scenarios on forecasts.

Spreadsheets and variety of BI tools will not solve these challenges alone. We need a much easier way of combining predictive techniques to solve these problems. With SAC you have these capabilities integrated together from preparing and combining data with Smart Wrangling in Datasets, creating predictive forecasts with Smart Predict and building What-If Analysis Scenarios in Stories. All in an iterative self-service process that can be tested quickly.

For more complex and deeper what-if scenarios analysis we can also provide ways of visual simulation capabilities with the Value Driver Tree and even more functions like pattern-based allocations or spreading that have been primarily used by finance planning users. However, these are functions that can be used in a broader scope of governed data driven scenario analysis.

Data Preparation: Smart Wrangling

SAP Analytics Cloud’s smart wrangling capabilities introduce a new self-service analytics experience giving the ability to easily iterate between question and insight. Data wrangling is the process of cleaning, structuring and enriching raw data into a desired format for better decision making in less time.

The business analyst can now create a complex calculation and build out a sequence of calculations to be conducted in a specific order and capture the answer at the end. This self-service model with data wrangling tools allows analysts to tackle more complex data more quickly, produce more accurate results, and make better decisions. Because of this ability, more businesses have started using data wrangling tools to prepare before analysis.

Smart Predict: Time Series Forecasting

After the data preparation step with smart wrangling, time series forecasting helps business analyst to make informed business decisions and go further in his self-service analytics experience, because it can be based on historical data patterns. It can be used to forecast future conditions and events.

What-If Analysis

What-If the business analyst would like to simulate different What-If type of scenarios on forecasted data?  The What-If Analysis is a decision-making method that helps to make the right decision and think about what impact it will have beforehand. It can also prevent that no single person alone can make decisions and a drive culture that several people are involved in the process. The What-If analysis is helpful here as well.

Value Driver Tree

From What-If Analysis we can go much further to understand how drivers impact outcomes; Evaluate business initiatives such as new product launch or new market entry; Identify opportunities for efficiency & improvement; and more. With VDT, the business analyst can deep dive into the impact of changes to one or more value drivers to operational or financial outcomes.

Collaborative Enterprise Planning with Predictive Forecasts

What if we would like to reach one source of truth, with SAP Analytics Cloud for Planning you can now align plans across organization to break down silos and bring teams together – finance, HR, sales, marketing, IT, and supply chain. Everyone can collaborate.

Finally, Predictive Planning, provides the ability to automate data-driven governed enterprise planning with time series forecasting through a tight integration. Predictive Planning is designed for self-service. This experience is targeted towards line of business users. It does not require IT (Information Technology) or data science abilities.

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  • What if the data set changes – do we have to redo the whole dataset again ? And what if new data needs to come in – is that still a manual task.

    what it depends on data – and currently data wrangling and getting new data into the dataset with very limited capabilities

    please fix the data side first – or else all of these efforts are pointless