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IBM Planning Analytics Tips & Tricks: Popular Video Tips, Part 2

August 15, 2023 by Revelwood

We’re continuing to highlight some of our most popular video tips & tricks for IBM Planning Analytics.

In this video, Revelwood’s FP&A Technology Director, Lee Lazarow, demonstrates how to create a button in Planning Analytics Workspace (PAW) for a TurboIntegrator (TI) script. Creating buttons like this will simplify tasks for your end users and create a much better end user experience.

You’ll learn how to go into properties, determine the button target, make that into a process, and then select and choose that process. The features in PAW allow you to select if you want prompts to appear and what controls you have over those prompts.

Formatting Views in PAW

Watch this video to see Lee demonstrate how to format views in Planning Analytics Workspace (PAW). You’ll learn how to manipulate your views by:

Making columns wider
Changing row heights
Changing fonts and text styles
Adding shading, and more

IBM Planning Analytics, which TM1 is the engine for, is full of new features and functionality. Not sure where to start? Our team here at Revelwood can help. Contact us for more information at info@revelwood.com. And stay tuned for more Planning Analytics Tips & Tricks weekly in our Knowledge Center and in upcoming newsletters!

IBM Planning Analytics Tips & Tricks: Performance Monitoring

August 8, 2023 by Andrew Chaves

IBM Planning Analytics contains a series of Performance Monitoring Control Cubes that let you record performance statistics for various aspects of your environment.

In Perspectives, this feature was enabled by right-clicking on the name of the server. But did you know that you can also control this in Planning Analytics Workspace via the tm1s.cfg control settings?

To enable the monitoring, go to the Administration area and then select the option for Databases. Once you have selected your database, click on “configuration.”

The performance monitor settings are found within the Administration settings and the Default sub area.

Once enabled (be aware that there may be an impact on performance when you use this), you will be able to use the results to help analyze your server performance.

IBM Planning Analytics Tips & Tricks: Expanding Sections of Stacked Dimensions

July 25, 2023 by Marc Assenza

Have you ever been in a situation where you have stacked dimensions in your view and only want to expand one section of it? In legacy Perspectives, an expansion of one area equates to an expansion of all areas. IBM Planning Analytics Workspace (PAW), version 87, introduced functionality that allows you to expand just one piece at a time.

Here is an example of a simple view that shows Actual Finance expenses by Company.

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By default, an expansion of the Finance department would show an expansion for all three companies.

A new icon has been added that will allow you to determine how you want to expand and collapse the elements within your view.

When clicked, you will have two options: Symmetrical and Asymmetrical.

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If we change the approach to Asymmetrical and then expand the departments within company 2, only a subset of the full view is expanded.

This approach will allow you to tighten your analysis and let your users focus on a subsection of your view while still easily having the ability to see the big picture.

IBM Planning Analytics Tips & Tricks: Creating Charts in Planning Analytics Workspace

July 18, 2023 by Revelwood

Charts can be an incredibly powerful tool for communicating complex data in an accessible and visually appealing way. In the world of enterprise planning, IBM Planning Analytics provides users with the ability to create detailed and informative charts through its workspace interface, Planning Analytics Workspace (PAW).

This blog post is based on a recent webinar on creating PAW charts in the New Experience. We explore some of the key features and techniques for creating charts in PAW and how they can help your organization make more informed decisions.

Getting Started: The Basics of PAW

Before getting into creating charts, it’s worth taking a quick look at the basics of PAW and how it works. PAW is a web-based interface that allows users to easily access and analyze data stored within IBM Planning Analytics. It includes a range of features and tools for exploration, analysis, and reporting, with the ability to create custom dashboards, reports, and visualizations.

PAW offers two different versions, Classic and the New Experience. While the Classic version is still available, the New Experience offers a more modern and intuitive user interface, with added applications and plans, Watson-related components, and changes to administration and charting functions.

Types of Visualizations

Once you have a basic understanding of PAW, it’s time to start exploring the different types of visualizations that can be created. PAW offers a variety of chart types that can help you visualize your data, including comparison, composition, and trend charts.

Comparison charts are useful when you want to compare two or more data series side-by-side, such as comparing actual versus forecasted revenue. Composition charts, on the other hand, are used to show the composition of a single data series, such as the breakdown of sales by product category. Trend charts are ideal for highlighting trends and patterns over time, such as changes in website traffic or sales revenue.

Creating a Chart: The Three Approaches

When it comes to creating a chart in PAW, there are three main approaches you can take. The first is to convert an existing Exploration to a chart, which can be done using drag-and-drop functionality and a subset editor. This approach is great when you already have an Exploration with the data you want to visualize.

The second approach is to duplicate an existing chart and make tweaks to it as needed. This is useful when you want to create multiple similar charts quickly without having to start from scratch each time.

Finally, the third approach is to manually create a visualization from scratch in a book. This approach allows for the most customization, as you can define the axes, filters, and formatting of the chart yourself.

Once you’ve chosen your approach, it’s time to start customizing your chart. PAW provides a range of options for bars, length, start, target, repeat, and filters, allowing you to fine-tune your visualization to best suit your needs. You can also add value labels to the chart to provide additional context and make it easier for viewers to understand the data being presented.

Tips for Effective Chart Design

While creating a chart in PAW is relatively straightforward, there are some best practices to keep in mind to ensure your chart is as effective as possible. Here are a few tips to consider:

Consider your audience: Who will be viewing your chart? Make sure the design and content are appropriate for your intended audience.
Keep it simple: Don’t try to cram too much information onto one chart. Focus on the key data points and keep the design clean and uncluttered.
Use the right chart type: Make sure you choose the chart type that best suits the data you are presenting and the story you want to tell.
Label everything: Be sure to label all axes, data points, and categories to ensure your chart is clear and easy to understand.
Use color wisely: Colors can be a great way to highlight important data points, but be sure to use them sparingly and consistently across all your charts.

Conclusion

Creating charts in PAW can be a powerful way to communicate complex data in a clear and accessible way. With a range of chart types and customization options, PAW provides users with the tools they need to create informative and visually appealing visualizations. Keep these tips in mind as you start experimenting with creating charts in PAW, and you’ll be on your way to creating clear, compelling reports that drive informed decision-making.

IBM Planning Analytics Tips & Tricks: Excel’s Camera Tool

July 11, 2023 by Ivan Cepero

The Linked Picture tool (aka Camera tool) is a little-known feature in Excel that you can use to give your dashboards and reports greater flexibility. In summary, the linked image is an image that is connected to the source data and updates automatically. You can resize and move the image without affecting the underlying source data.

To create a linked picture:

1 – Select the source area

2 – Copy the area

3 – Select another empty cell (this will be where you will paste the image)

4 – Select Paste Special > Linked Picture

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Excel will paste a picture that is linked to the original source area. You can verify the linkage by selecting the linked picture and looking at the formula bar, it will have the addresses of the source range.

Any changes applied to the source data will be reflected in the linked picture. This includes data updates, formatting changes, conditional formatting updates, objects (e.g., icons, charts, etc.) placed in the data source.

The linked image can be resized and moved into a report/dashboard for placement irrespective of column width or row height limitations.

IBM Planning Analytics Tips & Tricks: Headcount Analysis

June 27, 2023 by Revelwood

Did you miss our recent webinar on headcount analysis? Here’s a high-level recap of what we covered. In short, IBM Planning Analytics is a powerful, flexible tool for headcount analysis.

Headcount analysis is a critical component of any organization’s workforce planning and management strategy. Headcount analysis helps organizations understand their staffing requirements, analyze performance metrics, and identify areas of inefficiency that can be addressed through better HR practices. IBM Planning Analytics provides powerful capabilities for headcount analysis. In this blog post, we will explore headcount analysis with IBM Planning Analytics and discuss key features and benefits of this solution.

Watch the webinar here!

IBM Planning Analytics enables organizations to create sophisticated headcount models that can track a wide range of metrics related to employee performance, retention rate, demographics, compensation, and benefits. With Planning Analytics, organizations can analyze trends in headcounts, understand factors driving variations in headcounts, and identify opportunities to optimize their workforce. For example, you can use Planning Analytics to compare headcounts across different geographies or business units and to identify trends in staffing changes over time.

The solution provides a flexible and user-friendly interface that makes it easy for HR teams and other stakeholders to analyze headcount data. They do not need to be Planning Analytics power users. Planning Analytics includes a variety of pre-built dashboards, reports, and visualizations that enable users to explore and collaborate on data. Users can drill down into specific data points, filter data based on different criteria, and customize their views to suit their needs. The solution also includes a built-in report writer that enables users to create customized reports with ease.

IBM Planning Analytics integrates seamlessly with a variety of data sources, such as ERP and HR systems, to provide a holistic view of headcount data. This means that organizations can extract data from multiple sources and integrate it into a single model for analysis, without having to rely on complex data transformations or manual data entry. This integration capability also ensures that headcount data is accurate and up to date, which is essential for effective decision-making.

Additionally, IBM Planning Analytics provides advanced analytics features such as predictive analytics, what-if scenarios, and trend analysis that enable organizations to forecast future headcount requirements, costs, and risks. Predictive analytics models can use historical data and machine learning algorithms to predict future staffing demands and highlight areas of staffing volatility. What-if scenarios enable organizations to simulate the impact of different staffing strategies, such as hiring freezes or increased retention efforts. And trend analysis enables organizations to understand the impact of different factors on headcount, such as seasonality, economic trends, and business cycles.

The solution also provides robust collaboration and workflow capabilities that enable HR teams to work together effectively and efficiently. The solution includes a variety of collaboration features such as commenting, task assignment, and alerts that enable teams to share information and coordinate efforts. The solution also includes powerful workflow features that enable teams to automate routine tasks and streamline processes, such as approvals and reviews.

Finally, IBM Planning Analytics provides security features that ensure the confidentiality and privacy of headcount data. The solution includes granular access controls, data encryption, and other security measures that enable organizations to protect their sensitive data. The solution is also compliant with a variety of security and privacy regulations, such as GDPR and HIPAA.

In conclusion, headcount analysis is a critical component of any organization’s workforce planning and management strategy. IBM Planning Analytics is an advanced analytics solution that provides powerful capabilities for headcount analysis. The solution enables organizations to create sophisticated headcount models, analyze trends in headcounts, and forecast future headcount requirements, costs, and risks. The solution also provides a user-friendly interface, integrates seamlessly with a variety of data sources, provides advanced analytics features, enables robust collaboration and workflow, and includes security features that ensure the confidentiality and privacy of headcount data. If you’re looking to optimize your workforce and improve your HR practices, IBM Planning Analytics is a solution worth exploring. Interested in learning how to leverage your investment in Planning Analytics by adding headcount analysis into your environment? Let us know – we can help!

IBM Planning Analytics Tips & Tricks: Waterfall Charts

June 20, 2023 by Revelwood

Did you miss our webinar on waterfall charts in IBM Planning Analytics? Here’s our take on best practices and how and why to use waterfall charts.

Waterfall charts, also known as bridge charts, floating column charts, or cascade charts, are a data visualization tool used to represent changes in a value over time. They are particularly useful for showing how a specific value, such as a company’s profit or revenue, has changed from one period to another and the impact of different components on this change.

Waterfall charts are named after their appearance – the bars in the chart resemble a waterfall cascading downward. In a common example, the initial value is displayed as the starting point, and each segment of the waterfall represents the change in value due to certain factors. The length of each bar segment represents the size of the change, with upward bars indicating increases and downward bars representing decreases.

One of the advantages of using a waterfall chart is that it helps users easily identify the contribution of each component to the overall value. For example, a waterfall chart can show the contribution of different revenue streams to a company’s total revenue, thereby highlighting areas of strength and weakness in the company’s income stream.

Another common usage of waterfall charts is to show how an investment or project has affected the financial performance of a company. For instance, a waterfall chart can demonstrate the cost and revenue distribution of a new product development project over time. This can help in identifying areas where costs could be optimized or where revenue could be increased.

In enterprise planning and analytics, waterfall charts are crucial in depicting the impact of different scenarios, period-over-period comparisons, and identifying performance gaps. These charts allow professionals to identify key drivers of revenue or costs and identify areas that require improvement. It is also useful for businesses to use waterfall charts to identify performance trends, forecast trends based on prior data, and determine areas that require resource allocation.

Creating a Waterfall Chart

Creating a waterfall chart is relatively easy. A waterfall chart can include as many segments as required to represent the changes that need to be visualized.

To create a waterfall chart in Excel, start by creating a table that contains the total initial value and the changes in value. The table should represent a timeline that goes from left to right. The first column will contain a description of the different components that make up the initial value. The second column will display the size of the initial value. The subsequent columns will display the changes that occur within each segment. Each column will represent a change in the value of the previous column, either positive or negative. For example, a positive value could represent an increase in sales revenue, while a negative value could represent a rise in production costs.

Once the table has been created in Excel, the next step is to insert a waterfall chart. Select the table contents, including the initial value, then select “Insert” on the top menu bar and choose the “Waterfall Chart” type. The chart will then be created, showing each segment’s component and how it contributes to the overall value.

When using Planning Analytics, the process follows a similar outline. You will first need to create a table that houses the total initial value and the changes in value across time. The processes available with Planning Analytics are more user-friendly and automated than those of Excel, making the analysis of the chart trend even easier.

Waterfall charts are a critical representation tool in enterprise planning and analytics. They play a significant role in identifying the drivers of revenue or performance, identifying gaps in performance, and providing a retrospective review of trends in a business’s performance. Furthermore, the ability to create data-driven visualizations in IBM Planning Analytics and Microsoft Excel (amongst other tools) has allowed businesses to quickly adapt to new data insights. As a result, they are valuable tools in every data-savvy professional’s toolkit.

IBM Planning Analytics Tips & Tricks: Planning Analytics Workspace (PAx) Zoom Bar

June 13, 2023 by Lee Lazarow

One of the strengths of OLAP tools like IBM Planning Analytics is that you can create data sets that stack multiple dimensions together. Planning Analytics Workspace (PAW) allows you to easily convert those data sets into an easy-to-read visualization. Here is an example of a column chart that shows historical expense data by both time and company.

These charts can quickly become hard to read as you include more dimensions in your rows. To minimize this issue, PAW includes a feature to add a zoom bar to your line and column visualizations. This zoom bar lets you focus on a smaller area of the visualization.

The zoom option is enabled within the Chart section of the Properties.

Once enabled, a scroll bar will appear on your chart.

You can then drag the edges of the scroll bar to zoom into a specific area. Here is an example of the same chart with a focus on Quarter 2.

This approach will make your existing line and column charts more interactive and easier to use as you ask more questions about your existing data.

IBM Planning Analytics Tips & Tricks: Popular Posts, Part 2

May 30, 2023 by Revelwood

Earlier this month we shared three of our most popular IBM Planning Analytics Tips & Tricks blog posts. Since we publish these tips & tricks posts every Tuesday, we have plenty of tips you might have missed. Here are three more of our most popular posts over the last 12 months.

IBM Planning Analytics Tips & Tricks: Edit Action Button

Action buttons in IBM Planning Analytics are a great utility that allows users to recalculate a sheet, navigate to another location, or run a TurboIntegrator process. As your models evolve, you may need to periodically revise your templates to maintain their functionality. This sometimes include the action buttons. Read this post to learn how to quickly edit all of your action buttons at the same time instead of having to navigate through your workbook and search for each button.

IBM Planning Analytics Tips & Tricks: Adding a New Entry to Index Cube via Dynamic Report

If your IBM Planning Analytics model contains a cube that uses an index or slot dimension, you may encounter a situation where you’ll need to create a template that will allow your users to add data to an unused index. Read this post to see how to add a new entry in the index of a staffing cube.

IBM Planning Analytics Tips & Tricks: When to Build Multiple Cubes

We’ve had clients ask about the approach of building one cube for a model versus building multiple cubes for a model. A cube consists of a single table/database of data, whereas a model consists of a series of cubes that are linked together.

Planning Analytics (TM1) is designed to quickly and efficiently link a series of small cubes together. This style of thinking contradicts the approach that you may be used to with Excel. Read this post to learn more about building one cube versus multiple cubes.

IBM Planning Analytics Tips & Tricks: Popular Video Tips, Part 2

Read more IBM Planning Analytics Tips & Tricks:

IBM Planning Analytics Tips & Tricks: Performance Monitoring

Read more IBM Planning Analytics Tips & Tricks:

IBM Planning Analytics Tips & Tricks: Expanding Sections of Stacked Dimensions

Read more IBM Planning Analytics Tips & Tricks: