Power Bi Spend Analysis | Ask Questions Of The Data

Power BI Report

Report của Phượng Yến bao gồm 4 phần:

• Spending by Location: Thống kê chi tiêu cho hoạt động mua hàng của doanh nghiệp theo khu vực địa lý;
• Spending by Item: Thống kê chi tiêu cho hoạt động mua hàng của doanh nghiệp theo mặt hàng;
• Payment Term: Chính sách thanh toán cho các nhà cung cấp của doanh nghiệp;
• Cost Improvement: Thực trạng cải thiện chi phí cho hoạt động mua hàng.

Dưới đây là bản report trên Power BI của học viên:

What is an example of spend analysis?

An example of spend analysis could involve a manufacturing company looking to optimize its procurement process. The company collects data on all its purchases over the past year, categorizes spending into different areas (e.g., raw materials, maintenance services, office supplies), and analyzes the data.

During the analysis, the company might discover that it is overspending on certain raw materials due to unfavorable supplier contracts. This insight prompts them to renegotiate contracts, leading to significant cost savings. Additionally, they might identify inefficiencies in their office supplies procurement, enabling them to streamline the process and reduce unnecessary expenditures.

Vendor discounts

Let’s also explore the discounts available from vendors, and the time periods when we get the most discounts:

• Are the discounts different each month or do they remain the same?
• Do some cities get more discounts than others?

Discount by month

If you look at the Total Invoice and Discount % by Month combo chart, we see that February is the busiest month, and September is the least busy month.

Look at the discount percent during these months. When volume increases, the discount shrinks, and when volume is low, the discount increases. The more we need the discount, the worse of a deal we get.

Discount by city

Another area to explore is the discount by city. Select each city in turn see how the other charts change:

• St. Louis had a large spike in total invoices in February and a large dip in discount savings in April.
• Mexico City has the highest discount percentage (11.05%) and Atlanta has the smallest (0.08%).

What are the key success factors for a spend analysis initiative?

Key success factors for a spend analysis initiative include:

• Executive Support: Secure support and buy-in from top management.
• Data Quality: Ensure high-quality, clean, and reliable data.
• Skilled Personnel: Have a team of skilled analysts and data experts.
• Clear Objectives: Define clear objectives and goals for the analysis.
• Technology: Invest in the right technology and tools.
• Continuous Improvement: Continuously review and improve analysis processes.
• Actionable Insights: Translate analysis results into actionable strategies and decisions.

What is Power BI?

Microsoft’s Power BI software is dedicated to self-service Business Intelligence. This platform makes it easy to create visually appealing reports from data. It can also be used to create interactive tables that can be easily shared.There is a Desktop version of Power BI for local installation, and a Service version available via the cloud. The Power Query engine can be used to retrieve data from any source, thanks to a wide variety of connectors.

The DAX (Data Analysis Expressions) language enables queries to be programmed. Various tools and templates enable you to create reports and dashboards from data.

One of Power BI’s strengths is the creation of aesthetically pleasing reports and dashboards. In comparison, Microsoft Excel seems limited in terms of styles and options.

Thanks to the cloud, reports and dashboards can be shared very easily via the web. Teams can therefore collaborate on a project in an efficient and coordinated way. Visualizations can be opened on mobile platforms such as iOS and Android, or even on a connected watch.Various security features help to protect data. Another advantage over Excel is that Power BI prevents obsolete data from being shared, so that everyone has access to the latest version of the report or dashboard.

What is Excel?

The Excel spreadsheet application is world-renowned and offers many possibilities, including the creation of interactive dashboards in the style of Power BI. This software is particularly useful for quick analyses and calculations.

Using the VBA (Visual Basic for Applications) language, you can automate many tasks. Several free templates are available for creating dashboards.

However, dashboards created with Excel are less visually pleasing and don’t offer as many data filtering features. The advantage of Excel is that it offers far more diverse possibilities than Power BI. In particular, it is better suited to financial modeling and prediction.

With Excel, there is a risk of sharing obsolete data. However, such an incident can be avoided with sharing platforms such as OneDrive, SharePoint or Microsoft Teams.

Keep in mind that Excel is a general-purpose tool. This spreadsheet can also be used for data visualization or data scraping.

Differences and similarities between Excel and Power BI

Excel and Power BI use Power Query and Power Pivot. Mastery of these components is therefore an asset for both programs.

In fact, the two platforms integrate very well, since they were both created by Microsoft. A data model created in Excel can very easily be published in Power BI without transition.

Similarly, Excel and Power BI integrate seamlessly with other Microsoft Office applications, such as Teams and the Power ecosystem. This saves time and automates processes.

There’s really no need to choose between Excel and Power BI, as they work very well together. Generally speaking, Excel is ideal for exploring data, while Power BI is better suited to presentation and sharing.

The advantage goes to Power BI for sharing and collaborating dashboards and reports. All it takes is a few clicks.

Similarly, Power BI’s ability to analyze large volumes of data makes it the best option for data visualization. Its customized dashboards offer a 360-degree view, and alerts can be set on Key Performance Indicators.

In terms of interactivity and functions, Microsoft Excel is more limited for dashboards. Its tabular data format helps to visualize data in different chart formats, but it is not an ideal tool for larger data sets.

Power BI’s many features for formatting, natural language queries, editing or filtering make reports easier to understand, visually appealing, and highly dynamic and interactive.

How do I learn to use Power BI?

Power BI is now the most popular Business Intelligence solution, and will soon be as ubiquitous in the company as Excel. As such, mastery of this software is a highly sought-after business skill.

To learn how to use it, choose DataScientest. Our intensive training program enables you to learn how to use Power BI in just three days. The program modules cover an introduction to Power BI, data transformation with Power Query, the DAX language, data visualization and workspace management.

On completion of this course, you will be able to take the PL-300 exam and become a Microsoft Data Analyst Associate. A mock exam is also included in the program to help you prepare.

If you’re living in France, this course is eligible for funding under the Compte Personnel de Formation scheme. Don’t wait any longer and discover Power BI training!

Now you know everything there is to know about Excel and Power BI. Find out more about Power BI and Business Intelligence.

Thực hành Power BI theo dự án là một phần trong các khóa học Power BI và Data Analyst Foundation tại Datapot. Trước khi kết thúc mỗi khóa học, các học viên đều có cơ hội làm bài tập dự án để được thực hành giải quyết một vấn đề cụ thể do học viên tự lựa chọn và nhận được những nhận xét chi tiết đến từ ban giám khảo là những giảng viên, chuyên gia trong ngành Dữ liệu.

Dưới đây là bài tập dự án trong khóa học của học viên Cao Việt Phương.

Mục lục

Related content

This environment is a safe one to play in, because you can choose not to save your changes. But if you do save them, you can always return to the Learning center for a new copy of this sample.

We hope this tour has shown how Power BI dashboards, Q&A, and reports can provide insights into sample data. Now it’s your turn. Connect to your own data. With Power BI, you can connect to a wide variety of data sources. To learn more, see Get started creating in the Power BI service.

The Steps in Spend Analytics

Step 1: Analysis Scope and Data Collection

Before you look for data, you have to know what you want to find. An analytics review can be broad, all companies in a multi-national conglomerate, or narrow, direct spend for a manufacturer.

Finding data is relatively easy for smaller companies who may store the necessary data in a single ERP system. Larger companies may require access to ERPs, General Ledgers, eprocurement software, expense management solutions, and other specialized systems.

Like private equity and holding companies, companies with complex business structures may have a greater challenge due to the variety of software among their divisions, subsidiaries, and acquisitions.

Once you have set your review scope and identified the business systems that store the data, the next action is to bring the data altogether. How you do that depends on how frequently you intend to calculate the analytics.

If the analysis is a one-time or infrequent event, then exporting the data and collecting it in a spreadsheet, database, or spending analysis software is the easiest method.

If spend analytics will become a regular part of your procurement process, then using APIs and connectors to automate data extraction and loading may be worth the effort.

Step 2: Data Validation and Cleansing

Once the data has been collected together, it is validated for completeness and accuracy. Entries are consolidated, and fields are mapped to create a core data set. Data issues include missing fields, like descriptions, unreadable data, or partial data sets. The more complete the data, the better the analysis can be.

Data cleansing includes getting fields into a standard format. Entries with different formats for the same field lead to misunderstanding and big mistakes. For example, 02-05-20 can represent February 5, 2020, May 2, 2020, or May 20, 2002, depending on how you interpret numbers. Doing calculations using multiple currencies without aligning them will also lead to inaccurate results.

Step 3: Normalize Supplier Names

It’s common to call the same company by different names in different systems. It often varies based on who set the system up. After mergers or acquisitions, some companies retain their original name and become a subsidiary of another company. AI-driven analytics solutions and associate all versions of a company name to one normalized name. Normalizing supplier names is key to getting accurate assessments of total spend with any vendor. It helps identify places for establishing contracts or volume discounts.

Step 4: Item and Supplier Classification

Similar to normalization, classification tags items that are related. Using a taxonomy with a deep hierarchy for category management aids the data breakdown. KPIs and metrics for individual categories allow comparisons that drive savings insights. Both items and suppliers are classified to allow a narrow focus in the data.

Step 5: Data Enrichment

Data sets can be enriched by processing to create the KPIs and metrics that drive basic analysis – totals and averages, by supplier or category, trends, or year-over-year comparisons. These are all based on your data set.

Data can be enriched with external information, as well. Common added information includes certified diverse suppliers, procurement process benchmarks, and commodity pricing. The additional data can drive comparisons to industry standards or leaders and provide new targets to achieve.

Step 6: Visualization and Spend Analysis

The enriched data can be accessed in many ways but visualized in themed dashboards allows people to review areas of interest systematically. Procurement analysts know what to look for and, for example, go right to a commonality report if they want to consolidate purchases across fewer vendors.

These dynamic reports have filters that allow users, like category managers, to focus only on their interest area. Clicking around the reports can yield great savings ideas, but it can also be time-intensive.

Simfoni Spend Analytics provides automated opportunity analysis. The system reviews the common ways to save, identifies areas to save or improve, and grades it for estimated savings and difficulty to complete.

Analysts can accept the result or have the opportunity analysis focus on a particularly important area or a new KPI. The report shows the initiatives and the savings, and the order in which to do them!

Step 7: SAVE – Kick-off and Execute Procurement Initiatives

With your wave plan in hand, there is nothing left but assigning teams and kicking-off the initiatives. This may sound like many steps, but most of these can be done by software instead of humans if you pick the right Spend Analytics system.

Evaluate different cities

We can use highlighting to evaluate different cities.

1. Select the dashboard tile, Total Invoice, Discount % By Month, which opens the Discount Analysis page of the Procurement Analysis Sample report.

   If you’re using Power BI Desktop, select the Discount Analysis tab.

2. In the Total Invoice by City tree map, select each city in turn to see how they compare. Notice that almost all of Miami’s invoices are from tier 1 vendors.

Spend Visibility

Spend Analysis depends on accurate information from all purchasing-related data sources to effectively measure sourcing variables that took place over a period of time. Key Performance Indicators (KPIs) give direct measurements regarding the past and current state of the process. Be it a simple spreadsheet chart covering the last quarter, or Spend Analysis software with several years of data, KPIs and metrics provide the visibility needed to understand the procurement data.

After all, if you can’t see it, you won’t save it.

Data Gathering and Processing for Spend Analytics KPIs and Metrics

We all know the phrase “Garbage In, Garbage Out”. This is certainly true when it comes to analyzing procurement costs. Most procurement teams follow the following process to get the granular data needed for the most accurate results.

Identify all procurement and sourcing-related data sources.

Data sources can include general ledgers, ERP systems, e-procurement software, expense systems, P-cards, etc. Collect spend data from everywhere-all departments, business units, and manufacturing plants. Remember, it’s valuable to analyze both direct and indirect spending.

Gather the data into one, main location.

Compiling data can prove difficult since the data commonly is in different formats, different currencies, or different languages. Specifically designed extract, transform, load (ETL) procedures exist to overcome these issues. A Spend Analytics solution handles the variances and ETL automatically. When using spreadsheets, procurement analysts need to process the differences themselves or use a data management tool.

Cleanse data for more accurate processing.

Besides language and currency, product and supplier fields, such as names and descriptions, are compared and normalized to be the same. For example, three different business units may buy laptops from Dell each using a different supplier name—DELL, Dell Technologies, Dell, Inc. Standardizing sourcing data makes it easier for companies (and machines and algorithms) to interpret the data.

Enrich data for complete entries and additional metrics.

Data coming from varied sources will have different fields potentially causing issues when they are brought together. Common problems include missing specific fields, abbreviations, and misspellings. Smartly combining the data generates more complete entries for each item. Include outside data sources to enrich data for more ways to analyze, for example, industry codes, supplier diversity status, and ISO certifications.

Categorize items and materials into logical hierarchies.

Having all spending data in a unifying taxonomy allows procurement professionals to understand and track where the money is being spent. There are existing categorization standards, such as UNSPSC (United Nations Standard Products and Services Code), NAICS (North American Industry Classification System), or eClass. Regardless if a company uses its own classification system or variants of existing ones, all spend must be accurately categorized including marketing, travel, office supplies, and legal services. The deeper the categorization, the more granular and informative the spend analytics can be. Classification can be a tedious, detailed, months-long task. Using Spend Analytics software with an AI-powered classification engine can speed that process to days and categorize 60-70% of the first pass data automatically. After human review and correction, the system learns and improves, classifying a higher percentage each time. The ROI on analysis solutions like these can be nearly immediate – the savings in time and resources alone are tremendous.

Get the sample

Before you can use the sample, get the sample in one of the following ways:

• Get the built-in sample in the service.
• Download the .pbix file.

Get the built-in sample

1. Open the Power BI service (

   
app.powerbi.com

   ), and select Learn in the left navigation.

2. On the Learning center page, under Sample reports, scroll until you see the Corporate Spend sample.

3. Select the sample. It opens in Reading mode.

   Power BI imports the built-in sample, adding a report and semantic model to your current workspace.

Get the .pbix file for this sample

Alternatively, you can download the Corporate Spend sample as a .pbix file, which is designed for use with Power BI Desktop.

1. Open the GitHub Samples repository to the Corporate Spend sample .pbix file.

2. Select Download in the upper-right corner. The sample downloads automatically to your Downloads folder.

If you’d like to view it in the Power BI service, you can publish it there.

1. Open the file in Power BI Desktop and select File > Publish > Publish to Power BI or choose Publish in the Home ribbon.

2. In the Publish to Power BI dialog box, choose a workspace, and then Select.

   Power BI imports the sample, adding the report and semantic model to your selected workspace.

How can organizations ensure compliance through spend analysis?

To ensure compliance through spend analysis, organizations can:

• Define Procurement Policies: Establish clear procurement policies and guidelines.
• Automate Compliance Checks: Implement automated checks to ensure spending aligns with policies.
• Regular Audits: Conduct regular audits to identify and rectify non-compliance issues.
• Supplier Collaboration: Collaborate with suppliers to ensure contract adherence and compliance.
• Training and Education: Provide training and education to procurement teams on compliance requirements.

Final Thoughts: Empowering Your Stock Analysis with Power BI

Stock movement analysis is a complex and challenging task that requires a deep understanding of various factors influencing stock prices. By leveraging the power of Power BI, investors and businesses can gain a competitive edge in the stock market.

In this guide, we have covered the importance of stock movement analysis, the benefits of using Power BI, setting up Power BI, exploring the stock movement analysis dashboard, analyzing historical stock data, applying filters and slicers, utilizing Power Query for data transformation, creating custom calculated measures, leveraging DAX formulas, integrating external data sources, sharing and collaborating on reports, and overcoming common challenges.

By following this step-by-step guide and leveraging the features of Power BI, you can enhance your stock movement analysis capabilities and make more informed investment decisions.

Remember, stock markets are volatile, and stock analysis requires continuous learning and adaptation to changing market conditions. Stay updated with the latest trends and innovations in stock movement analysis with Power BI to stay ahead in the ever-evolving financial landscape.

Wishing you success in your stock movement analysis endeavors!

One of the key advantages of using Power BI for stock analysis is its ability to provide real-time data updates. With Power BI, investors can access up-to-date information on stock prices, market trends, and news that can impact their investment decisions. This real-time data integration allows for more accurate and timely analysis, giving investors a competitive edge in the fast-paced stock market.

In addition to real-time data updates, Power BI also offers advanced visualization capabilities. Users can create interactive charts, graphs, and dashboards that make it easier to analyze and interpret complex stock data. These visualizations can help investors identify patterns, trends, and correlations that may not be immediately apparent in raw data. By presenting data in a visually appealing and intuitive manner, Power BI enables investors to gain deeper insights into stock movements and make more informed decisions.

Download the Spend Analysis Handbook

Table of Contents

Spend Analysis

Spend analysis is the process of reviewing current and historical spending. The goal of the exercise is to reduce cost, improve strategic sourcing, and increase the efficiency of spend management. An analysis requires spend data processed into KPIs and metrics and then visualized to show patterns.

An analysis is most effective when the data meets the following criteria:

• Retrieved from all sourcing, procurement, and financial transaction software databases. (including ERP, General Ledger, eProcurement, and expense management)
• Normalized so that it can be correctly associated and rolled up.
• Classified based on a hierarchical taxonomy that groups to detailed levels, preferably to the item level.
• Enriched to ensure all required fields are complete.
• Processed by an AI engine, a business rules engine, and human spend analysts who know the data set very well.

With these data conditions, there is a much higher likelihood that the analysis will be accurate and granular enough to provide actionable insights. The data processing will also be significantly faster than a human with a simple rules-engine or spreadsheet.

Traditionally, spend analysis is labor and time-intensive, taking months to complete. This length of time makes it inconvenient to do the evaluation more than once or twice a year. That forces the procurement team to work with out-of-date data and little visibility into the impact of their in-progress initiatives.

Using an AI engine to process the data, completion time can shrink to a few weeks or even a few days. When repeated many times a year, spend analytics software can track the outcome of the initiatives to compare against original goals. Procurement can make adjustments based on new inputs from up-to-date data, making spend analysis a more useful and strategic exercise.

What is spend analysis?

Spend analysis is defined as the process of systematically reviewing both current and historical spending within an organization. This process involves several key components:

1. Data Collection: Gathering expenditure data from various sources across the organization.

2. Data Cleaning: Ensuring the accuracy and reliability of the collected data by eliminating errors and inconsistencies.

3. Data Classification: Categorizing and classifying spending data into different groups and categories.

4. Data Analysis: Using analytical tools and techniques to analyze the categorized spending data.

The primary objectives of spend analysis include:

1. Cost Reduction: Identifying opportunities to reduce costs and optimize spending.

2. Efficiency Improvement: Streamlining procurement processes and enhancing efficiency.

3. Strategic Sourcing: Supporting strategic sourcing efforts by providing insights into spending patterns.

4. Supplier Relationship Enhancement: Strengthening relationships with suppliers by making informed decisions based on spending data.

Spend analysis helps organizations extract maximum value from their procurement expenditures by providing visibility into how money is spent and where improvements can be made. It answers crucial financial questions, such as what the organization is spending money on, who the money is being spent with, whether value for money is being achieved, and if there are better procurement options available.

In essence, spend analysis is a data-driven approach that aids organizations in making informed decisions, optimizing their procurement processes, and ultimately achieving cost savings and efficiency improvements.

Edit the report

Select Edit in the black Power BI header bar to explore in the editing view:

• See how the pages are made, the fields in each chart, and the filters on the pages.
• Add pages and charts, based on the same data.
• Change the visualization type for each chart.
• Pin charts of interest to your dashboard.

Get the sample

Before you can use the sample, you must first get the sample in one of the following ways:

• Get the built-in sample in the Power BI service.
• Download the .pbix file.
• Download the Excel workbook.

Get the built-in sample

1. Open the Power BI service (

   
app.powerbi.com

   ), and select Learn in the left navigation.

2. On the Learning center page, under Sample reports, scroll until you see the Procurement Analysis Sample.

3. Select the sample. It opens in Reading mode.

4. Power BI imports the built-in sample, adding a new dashboard, report, and semantic model to your current workspace.

   Select the dashboard to view the sample dashboard.

Get the .pbix file for this sample

Alternatively, you can download the Procurement Analysis sample as a .pbix file, which is designed for use with Power BI Desktop.

1. After you open the file in Power BI Desktop, select File > Publish > Publish to Power BI or choose Publish in the Home ribbon.

2. In the Publish to Power BI dialog, choose a workspace and then Select.

3. In the Power BI service, in your workspace, scroll down to the Procurement Analysis Sample report and select to open.

4. From the More options (…) menu, select Pin to a dashboard. Select New dashboard, enter a name, and choose Pin live.

The dashboard that you create this way isn’t the same as the sample dashboard created by the built-in sample. You can still use Q&A and make changes to your dashboard.

Get the Excel workbook for this sample

If you want to view the data source for this sample, it’s also available as an Excel workbook. To see the raw data, enable the Data Analysis add-ins, and then select Power Pivot > Manage.

If you want to get and use the Excel file in the Power BI service, follow these steps:

1. Download the sample from Power BI Desktop samples. The file is called Procurement Analysis Sample-no-PV.xlsx.

2. Open the file in Excel and then select File > Publish > Publish to Power BI.

3. Select a workspace, such as My workspace, and choose Export.

   There are different ways to work with Excel files. For more information, see Explore the Excel samples in Excel.

4. In the Power BI service, the exported data appears as a semantic model in the selected workspace. Select More options (…) > Auto-create report.

5. Select Save, enter a name for your report, and then choose Save.

6. From the More options (…) menu, select Pin to a dashboard. Select New dashboard, enter a name, and choose Pin live.

The dashboard that you create this way isn’t the same as the sample dashboard created by the built-in sample. You can still use Q&A and make changes to your dashboard.

Get the sample

Before you can use the sample, get the sample in one of the following ways:

• Get the built-in sample in the service.
• Download the .pbix file.
• Download the Excel workbook.

Get the built-in sample

1. Open the Power BI service (

   
app.powerbi.com

   ), and select Learn in the left navigation.

2. On the Learning center page, under Sample reports, scroll until you see the IT Spend Analysis Sample.

3. Select the sample. It opens in Reading mode.

4. Power BI imports the built-in sample, adding a new dashboard, report, and semantic model to your current workspace.

   Select the dashboard to view the sample dashboard.

Get the .pbix file for this sample

Alternatively, you can download the IT Spend Analysis sample as a .pbix file, which is designed for use with Power BI Desktop.

1. After you open the file in Power BI Desktop, select File > Publish > Publish to Power BI or choose Publish in the Home ribbon.

2. In the Publish to Power BI dialog, choose a workspace and then Select.

3. In the Power BI service, in your workspace, scroll down to the IT Spend Analysis Sample report and select to open.

4. From the More options (…) menu, select Pin to a dashboard. Select New dashboard, enter a name, and choose Pin live.

The dashboard that you create this way isn’t the same as the sample dashboard created by the built-in sample. You can still use Q&A and make changes to your dashboard.

Get the Excel workbook for this sample

If you want to view the data source for this sample, it’s also available as an Excel workbook. To see the raw data, enable the Data Analysis add-ins, and then select Power Pivot > Manage.

If you want to get and use the Excel file in the Power BI service, follow these steps:

1. Download the sample from Power BI Desktop samples. The file is called IT Spend Analysis Sample-no-PV.xlsx.

2. Open the file in Excel and then select File > Publish > Publish to Power BI.

3. Select a workspace, such as My workspace, and choose Export.

   There are different ways to work with Excel files. For more information, see Explore the Excel samples in Excel.

4. In the Power BI service, the exported data appears as a semantic model in the selected workspace. Select More options (…) > Auto-create report.

5. Select Save, enter a name for your report, and then choose Save.

6. From the More options (…) menu, select Pin to a dashboard. Select New dashboard, enter a name, and choose Pin live.

The dashboard that you create this way isn’t the same as the sample dashboard created by the built-in sample. You can still use Q&A and make changes to your dashboard.

What role does technology play in spend analysis?

Technology, including spend analysis tools and data analytics software, plays a significant role in automating and enhancing the spend analysis process. It helps by:

• Efficiency: Automating data collection, cleansing, and categorization processes, saving time and reducing errors.
• Data Visualization: Providing visual representations of spending data for better insights and decision-making.
• Real-time Analysis: Enabling organizations to analyze spending patterns in real time for proactive decision-making.
• Predictive Analytics: Using historical data to predict future spending trends and identify opportunities for cost savings.
• Compliance Monitoring: Automating compliance checks to ensure adherence to procurement policies and regulations.

What are the common challenges in spend analysis?

Some common challenges in spend analysis include:

• Data Quality: Ensuring data accuracy, completeness, and consistency.
• Data Integration: Integrating data from various sources and systems.
• Data Volume: Handling and analyzing large volumes of data.
• Talent and Skills: Having skilled analysts who can interpret data effectively.
• Technology Adoption: Implementing and maintaining the right spend analysis tools.
• Change Management: Overcoming resistance to changes in procurement processes.

What are the types of spend analysis?

There are several types of spend analysis, including:

• Strategic Spend Analysis: Focuses on identifying long-term cost-saving opportunities and improving overall procurement strategies.
• Operational Spend Analysis: Concentrates on day-to-day spending to enhance efficiency and compliance with procurement policies.
• Supplier Spend Analysis: Analyzes spending patterns with specific suppliers to evaluate their performance and negotiate better terms.
• Category Spend Analysis: Examines spending within specific product or service categories to identify cost-saving opportunities and supplier consolidation possibilities.
• Contract Compliance Analysis: Ensures that spending aligns with the terms and conditions of supplier contracts.

The type of spend analysis chosen depends on an organization’s goals and the areas it wants to improve.

Setting Up Power BI: Getting Started with Data Import and Connection

Before diving into stock movement analysis with Power BI, you need to set up the tool and connect it to your data sources. Power BI supports a wide range of data connectors, including popular financial databases, spreadsheets, and online platforms. By connecting to your desired data source, you can import the relevant stock data into Power BI for analysis.

Once the data is imported, you can use Power BI’s intuitive data modeling capabilities to reshape and transform the data, ensuring it is in a suitable format for analysis. This step is crucial for preparing the data for visualizations and deriving meaningful insights.

After preparing the data, you can start creating visualizations in Power BI to gain insights into stock movements. Power BI offers a variety of visualization options, such as line charts, bar charts, and scatter plots, which can be customized to display the data in a visually appealing and informative way. Additionally, you can create interactive dashboards and reports that allow you to explore the data further and uncover patterns or trends.

Metrics that are included in the Power BI content

The Purchase spend analysis Power BI content includes a report that consists of a set of metrics. These metrics are visualized as charts, tiles, and tables.

The following sections provide an overview of the visualizations.

Purchase by vendor report page

Charts

• Top 10 vendors by purchase (stacked bar chart)
• Total purchase by vendor group / country/region / name (pie chart)
• Purchase by vendor group / country/region / name (column chart)
• Average purchase by vendor group / country/region / name (column chart)

Tiles

• Total purchase
• YOY purchase growth
• Total # vendors
• Total # of active vendors

Example

Purchase by product report page

Charts

• Purchase by procurement category / product name (column chart)
• Total purchase by procurement category / product name (pie chart)
• Top 10 products by purchase (stacked bar chart)

Tiles

• Total # of products
• Total active products percentage of total # of products
• Number of products accounting for 80% purchase

Example

Purchase by period report page

This page shows purchases this year and last year, and growth by procurement category.

Charts

• Purchase by month / day (column chart)
• Cumulative purchase YOY variance (waterfall chart)
• Total purchase YOY growth (column chart)
• Procurement statement (matrix)

Tiles

• YOY purchase growth
• YOY purchase growth %

Example

Purchase by vendor location report page

Charts

• Purchase by city
• Purchase YOY growth %
• Purchase by country/region

Example

Purchase spend analysis by time report page

Charts

• Purchase current year by month / day (line chart)
• Purchase current and last year (line and column chart)

Example

Purchase spend analysis by vendor report page

Charts

• Top 10 vendor purchase % of purchase (funnel)
• Top 10 vendors with increased spending YOY
• Top 10 vendors with decreased spending YOY

Example

What is Spend Analysis?

Spend analysis is the process of reviewing current and historic corporate spending with the goal of identifying cost reduction opportunities, improving strategic sourcing, and reducing procurement costs.

Spend analysis has three main parts:

1. Spend Visibility– Having clean spend data as well as KPIs and other metrics as a way to see spending from many points of view.
2. Spend Analysis– Asking questions about corporate spending and procurement, finding the answers in the metrics, and creating ways to reduce costs and improve results.
3. Procurement Process Improvement– Taking the results of the analysis and implementing changes to improve future performance meeting corporate goals.

Introduction to Power BI: A Powerful Tool for Stock Analysis

Power BI is a business intelligence tool developed by Microsoft. It enables users to connect to various data sources, transform data, and create interactive visualizations and reports. Power BI provides a user-friendly interface and powerful data modeling capabilities, making it an excellent choice for stock movement analysis. With its extensive range of visualizations and advanced analytical features, Power BI empowers users to explore and interpret their stock data effectively.

One of the key advantages of using Power BI for stock analysis is its ability to handle large volumes of data. Stock data can be vast and complex, with multiple variables and time series. Power BI’s robust data modeling capabilities allow users to efficiently organize and manage this data, enabling them to perform in-depth analysis and uncover valuable insights.

What is a spend analysis tool?

A spend analysis tool is software designed to automate and facilitate the process of collecting, cleansing, categorizing, and analyzing spending data within an organization. These tools are essential for organizations with large volumes of data as they provide efficient and accurate ways to gain insights into spending patterns.

Spend analysis tools often offer features such as data visualization, reporting, supplier performance tracking, and trend analysis. They can help organizations identify cost-saving opportunities, optimize procurement strategies, and ensure compliance with procurement policies.

Data model and entities

The following data is used to fill the report pages in the Purchase spend analysis Power BI content. This data is represented as aggregate measurements that are staged in the Entity store. The Entity store is a Microsoft SQL Server database that is optimized for analytics. For more information, see Power BI integration with Entity store.

The aggregate measurements in this content are the subset of aggregate measurements that were available in the Purchase Cube in Microsoft Dynamics AX 2012 and Microsoft Dynamics AX 2012 R3. To stage the cube’s aggregate measurements in the Entity store, you must make them deployable. For more information, see the procedure for staging aggregate measurements in the Entity store in Power BI integration with Entity store. The following key aggregate measurements are available directly from the Invoice lines entity and are used as the basis of the content.

Entity	Key aggregate measurements	Data source	Field	Description
Invoice lines	Purchase	VendInvoiceTrans	SUM(LineAmountMST)	The amount in the accounting currency.

The following table shows the key measurements in the content that are calculated from the Invoice lines entity.

Measure	Calculation
Purchase current year	Purchase current year = SUM(‘Invoice lines'[Purchase])
Purchase last year	Purchase last year = CALCULATE(SUM(‘Invoice lines'[Purchase]), SAMEPERIODLASTYEAR(Dates[Date]))
YOY purchase growth	YOY purchase growth = [Purchase current year] – [Purchase last year]

The following key dimensions in the content are used as filters to slice the aggregate measurements, so that you can achieve more granularity and gain deeper analytical insights.

Entity	Examples of attributes
Vendors	Vendor groups, Vendor country or regions, Vendor name
Products	Product number, Product name, Item groups name
Procurement categories	Procurement category, Procurement category names
Legal entities	Legal entity name
Dates	Dates, Year offset

By default, the content shows data for the current calendar year. However, you can change the date filter in the report filters section. You can also change the company filter.

Spend Analysis

From purchase price variance to supplier diversity to items purchased across- business units, there are actionable insights in almost every area from the spend analysis process. The information leads to smarter, data-driven, business decisions regarding the purchases made in every part of an organization. The outcome of the analysis is a set of initiatives that will help improve purchasing efficiency, save cost, and reduce supply risk.

Ask questions of the data

1. In the dashboard, select Ask a question about your data.

2. From the Try one of these to get started list on the left side, select top cost element groups by plan.

3. In the Q&A box, clear the previous entry and enter show IT areas, var plan % and var le3 % bar chart.

   In the first IT area, Infrastructure, the percentage has changed drastically between the initial variance plan and the variance plan latest estimate.

What are the best practices for data collection in spend analysis?

Efficient data collection is fundamental to ensuring the precision of spend analysis. Here are some recommended approaches:

Diverse Data Sources: Aggregate data from a range of origins, encompassing invoices, purchase orders, contracts, and supplier databases, to establish a comprehensive dataset.

Uniform Data Standards: Standardize data formats, codes, and units of measurement to maintain uniformity and precision.

Regular Data Validation: Continually validate data to pinpoint and rectify any errors or inconsistencies promptly.

Holistic Data Integration: Combine data from disparate departments or systems to construct a comprehensive overview of spending.

Timely Data Collection: Gather data at regular intervals to guarantee it accurately represents prevailing spending patterns.

Spending trends

First, let’s look for trends in spending by category and location.

1. In the Power BI service, find the workspace where you saved the sample. Select the Procurement Analysis Sample report, then the Spend Overview page.

   If you’re using Power BI Desktop, open the .pbix file and select the Spend Overview tab.

Note the following details:

• In the Total Invoice by Month and Category line chart, the Direct category has consistent spending, Logistics has a peak in December, and Other has a spike in February.
• In the Total Invoice by Country/Region map, most of our spending is in the United States.
• In the Total Invoice by Sub Category column chart, Hardware and Indirect Goods & Services are the biggest spend categories.
• In the Total Invoice by Tier bar chart, most of our business is done with our tier 1 (top 10) vendors. Doing so enables us to manage better vendor relationships.

Spending in Mexico

Let’s explore the spending areas in Mexico.

1. In the Total Invoice by Country/Region map, select the Mexico bubble. Notice that in the Total Invoice by Sub Category column chart, most spending is in the Indirect Goods & Services sub category.

2. Drill down into the Indirect Goods & Services column:

   • In the Total Invoice by Sub Category chart, select the drill-down arrow

     in the upper-right corner of the chart.

   • Select the Indirect Goods & Services column.

     As you can see, the highest spending by far is for the Sales & Marketing subcategory.

   • Select Mexico in the map again.

     For Mexico, the biggest spending is in the Maintenance & Repair subcategory.

3. Select the up arrow on the upper-left corner of the chart to drill back up.

4. Select the drill-down arrow again to turn off the drill-down feature.

5. In the top navigation pane, select Procurement Analysis Sample to return to the dashboard.

How often should organizations perform spend analysis?

The frequency of spend analysis varies according to the organization’s objectives and the characteristics of its expenditures. Typically, organizations conduct annual spend analyses as an integral component of their strategic planning. However, some organizations opt for more frequent assessments, like quarterly or semi-annual reviews, to continuously track expenditure trends and adapt as necessary.

Procurement Process Improvements

The implementation process begins here as each initiative is assigned an owner and the activity begins. There are several common ways to make improvements, particularly in vendor management including:

• Improved item pricing and contract terms when business units buy through the same contract.
• Increase efficiency by reducing the number of suppliers for particular items or categories.
• Stronger supplier negotiation position from internal and external pricing benchmarks.
• Reduce processing time for purchase orders.

Some newer metrics are driven from internal and external compliance, like

• Level of spending on diverse suppliers—minority-, women, and veteran-owned businesses—both Tier 1 and Tier 2.
• Quality, Security, and Safety Compliance – ISO, SOX, SOC2, UL, N95
• ESG (Environmental, Social, and Governance) Initiatives

In order to measure the improvement, another analysis needs to be executed. This is not a problem when using a good spend analysis tool. Processing additional data should be fast and highly accurate based on the previous analysis. Processing the latest data provides real-time results that can show the progress made for each initiative.

Mục tiêu của project

Mục tiêu của dự án về Procurement Analysis – Phân tích nghiệp vụ mua hàng trên Power BI của học viên Dương Thị Phượng Yến là:

• Giúp cho ban lãnh đạo doanh nghiệp nhìn nhận lại các KPI hiện tại về mua hàng của từng bộ phận, từ đó đánh giá và thiết lập lại bộ KPI cho nghiệp vụ mua hàng tại doanh nghiệp;
• Chỉ ra thực trạng của hoạt động Procurement (Mua hàng) tại doanh nghiệp, từ đó giúp ban lãnh đạo xây dựng lại quy trình và kế hoạch mua hàng tối ưu hơn;
• Hỗ trợ các bộ phận liên quan ra quyết định mua hàng.

Understanding the Importance of Stock Movement Analysis

Stock movement analysis involves studying the fluctuations in stock prices over time and identifying patterns and trends. It helps investors gain insights into the performance and future prospects of a particular stock or the overall market. By analyzing stock movements, investors can make informed decisions about buying, selling, or holding stocks. This analysis is essential for maximizing profits, minimizing risks, and making strategic investment decisions.

Furthermore, stock movement analysis can also provide valuable information about market sentiment and investor behavior. By examining the volume of trades and the speed at which stocks are bought or sold, analysts can gauge the level of interest and confidence in a particular stock or the market as a whole. This information can be used to anticipate market trends and identify potential opportunities or risks.

What are the 4 stages in spend analysis?

Spend analysis typically consists of four key stages:

1. Data Collection: The first stage involves gathering data from various sources within an organization. This data can include invoices, purchase orders, contracts, and supplier information. The goal is to compile a comprehensive dataset that covers all aspects of spending.
2. Data Cleansing: Once the data is collected, it needs to be cleaned and standardized. This stage involves removing duplicates, correcting errors, and ensuring consistency in data format. Clean data is essential for accurate analysis.
3. Data Classification: In this stage, the spending data is categorized into different groups or categories. This classification helps identify where and how money is being spent. Common categorizations include direct and indirect spending, categories like raw materials, services, and capital expenditures, and supplier segmentation.
4. Data Analysis: The final stage involves analyzing the categorized spending data to gain insights and make informed decisions. This analysis can include identifying cost-saving opportunities, negotiating better contracts with suppliers, optimizing procurement processes, and ensuring compliance with policies.

The Power of a Spend Analysis

As spend analysis moves from a daunting months-long project to a task that takes a week, or a few days, the benefits to organizations increase tremendously. The following are reasons to use spend analysis and some new value gained when making it a regular procurement activity.

Improve Data Quality

The first part of a spend analysis involves gathering, cleaning, normalizing, and enriching the ALL the purchasing data. If you only use a subset of the data, you limit your review and ability to get useful results. Using data that is not scrubbed means the analysis will have duplicate items and suppliers, preventing paths for consolidation of suppliers. Remember‚ Garbage In = Garbage Out.

Increase Opportunities to Save

When you have all the data clean, you have a firm base to find trends, measure KPIs, and benchmark performance. The data needs to be classified, the deeper, the better to highlight these trends and actionable insights.

Use a Classification Taxonomy

Standard taxonomies are available, including UNSPSC (United Nations Standard Products and Services Code) and eClass. Simfoni has created standard taxonomies for several industries based on working with clients for over ten years and provides them as an option to new customers. Each company must decide if the taxonomy matches its business and is complete enough to provide useful analytics.

For example, within Level 1 category Facilities, you can find Building Maintenance on Level 3 [Facility > Facility Services > Building Maintenance]. If an analysis showed that your Building Maintenance spending is significantly higher than benchmarks, it would be a target for cost reduction. With no other information, the initiative would have to dig to understand what building maintenance aspect could cause the high cost. Uncovering the source could take a long-time considering Building Maintenance has over eight very different subcategories (See diagram below).

However, if the taxonomy classifies Facilities to Level 4, the initiative could focus and be more straightforward. At Level 4, the categories are specific enough to have just a few vendors each. The analysis can guide you to the vendors or products that are more expensive than they should be. The deeper the categorization, the more granular and informative the spend analytics can be. Level 4+ categorization and granular data lead to faster problem identification and increased procurement savings.

Improve Performance with Benchmarking

Having a deep taxonomy and clean classified data means that you can easily make comparisons to evaluate procurement performance. Internal comparisons between business units or locations can help identify and address spending outliers within your organization. Procurement process KPIs can also be compared to improve efficiency, like time to have a PO signed off.

To improve even more, use third-party benchmarks to enrich your data and make comparisons to businesses in your industry or of similar size. Some software providers, such as Simfoni Spend Analytics, offer first-party data as well. Whatever kind of benchmarking you choose to do, it can help reduce material and supply costs through price reductions, as well as the cost of doing business through efficiency gains.

Managing Supplier Risks and Relationships

Supplier relationships go best when there is a human element of trust and understanding of each other. That doesn’t mean you shouldn’t arm yourself with a detailed analysis.

A procurement analysis can identify the commonality of suppliers and products across departments or business units. Combine this with the ability to see how much of this spend is under contract or not. Walk into negotiations prepared with data that can lead to volume discounts, better payment terms, and more spend under contract. The broad visibility into suppliers allows for more strategic sourcing options.

In recent years, the supply of materials and parts has been disrupted by regional and worldwide events. In 2011, a 9.0 earthquake and tsunami hit Japan, causing the Fukushima Daiichi Nuclear Power Plant disaster, which disrupted the world supply of IC chips and automotive parts from Japan. And the COVID-19 outbreak in 2020 closed all manufacturing plants in China for months. Manage the supply chain risk by evaluating where you use single-source materials or where all vendors are from the same region of the world. For example, many companies needed to spot buy personal protective equipment (PPE) from sources located outside of China when the Chinese manufacturing plants were suddenly closed.

Some of the new areas of supplier management come from internal and external governance and compliance rules. Quality, Security, and Safety standards have been in place for a long time – ISO 9001(Manufacturing Quality), ISO 13485 (Medical Devices), UL V-0 (Material Flammability), Sarbanes-Oxley (aka SOX) and SOC (Financial Data & Computer Security).

Environmental, Social, and Governance (ESG) standards have been growing in popularity. The increasing level of spending on diverse suppliers—minority-, women-, and veteran-owned businesses- is tracked because there is a public demand for change and a need for measurement and transparency. Many companies who have government contracts require tracking both Tier 1 (Direct Diverse Spending) and Tier 2 (Diverse Spending by Tier1 Suppliers) because they get credit for both, and diversity compliance in some cases. These metrics are easy to analyze when you include diversity certifications in the data enrichment process.

What are the benefits of category spend analysis?

Category spend analysis offers several benefits, including:

• Cost Reduction: Identifying cost-saving opportunities within specific spending categories.
• Supplier Consolidation: Evaluating the potential for consolidating suppliers within a category.
• Risk Management: Assessing risks associated with specific categories and taking appropriate measures.
• Strategic Sourcing: Informing strategic sourcing decisions within categories.
• Performance Tracking: Monitoring supplier performance within each category.

IT Spend Analysis Sample dashboard

If you used the built-in sample, the two numbers tiles on the left of the dashboard, Var Plan % and Variance Latest Estimate % Quarter 3, give you an overview of how well we’re doing against the plan and against the latest quarterly estimate (LE3 = latest estimate quarter 3). Overall, we’re about 6% off the plan. Let’s explore the cause of this variance: when, where, and in which category.

YTD IT Spend Trend Analysis page

When you select the Var Plan % by Sales Region dashboard tile, it displays the YTD IT Spend Trend Analysis page of the IT Spend Analysis Sample report. At a glance, we see that there’s positive variance in the United States and Europe and negative variance in Canada, Latin America, and Australia. The United States has about 6% +LE variance and Australia has about 7% -LE variance.

However, just looking at this chart and drawing conclusions can be misleading. We need to look at actual dollar amounts to put things in perspective.

1. Select Aus and NZ in the Var Plan % by Sales Region chart, and then observe the Var Plan by IT Area chart.

2. Now select USA. Notice that Australia and New Zealand are a very small part of our overall spending as compared to the United States.

   Next, explore which category in the USA is causing the variance.

YTD Spend by Cost Elements page

1. Return to the dashboard and look at the Variance Plan %, Variance Latest Estimate % – Quarter 3 dashboard tile.

   Notice that the Infrastructure area stands out with a large positive variance to the plan.

2. Select this tile to open the report and view the YTD Spend by Cost Elements page.

3. Select the Infrastructure bar in the Var Plan % and Var LE3 % by IT Area chart on the lower right, and observe the variance-to-plan values in the Var Plan % by Sales Region chart on the lower left.

4. Select each name in turn in the Cost Element Group slicer to find the cost element with the largest variance.

5. With Other selected, select Infrastructure in the IT Area slicer and select subareas in the IT Sub Area slicer to find the subarea with the largest variance.

   Notice the large variance for Networking. Apparently the company decided to give its employees phone services as a benefit, even though this move wasn’t planned for.

Ask questions of the data

A dashboard offers the ability to ask questions about data in natural language to create visuals. It doesn’t matter how you create your dashboard or which tiles it has. You can ask questions about any semantic model attached to your dashboard.

1. In the dashboard, select Ask a question about your data. Power BI suggests several questions as starting points.

2. From Try one of these to get started, select top cost element groups by var plan.

3. In the Q&A box, clear the previous entry and enter what is the plan and var plan % by cost element sub group.

   Hover over a point for details and values.

4. Select Exit Q&A to return to the dashboard.

Why do we do spend analysis?

Spend analysis is crucial for several reasons:

• Cost Reduction: It helps identify cost-saving opportunities, such as negotiating better contracts with suppliers and eliminating unnecessary expenditures.
• Risk Mitigation: By analyzing spending patterns, organizations can identify potential risks and take preventive measures, such as diversifying their supplier base.
• Supplier Performance: Spend analysis allows organizations to evaluate supplier performance and make informed decisions about supplier relationships.
• Compliance: It helps ensure that spending aligns with procurement policies and regulations, reducing the risk of non-compliance.
• Strategic Insights: It provides valuable insights for long-term strategic planning and decision-making.

Benefits of Using Power BI for Stock Movement Analysis

Power BI offers several benefits for stock movement analysis:

1. Visualize Complex Data: Power BI allows users to create interactive visualizations, charts, and graphs to represent complex stock data in an intuitive and understandable format.
2. Data Exploration: With Power BI, users can drill down into the data, filter it, and view the stock performance from various angles, uncovering hidden insights.
3. Real-Time Monitoring: Power BI enables users to connect to live data sources and monitor stock movements in real-time, enabling quick decision-making.
4. Data Integration: Power BI allows users to integrate various data sources, such as financial databases, online marketplaces, and external APIs, for a comprehensive stock movement analysis.

These benefits make Power BI a valuable tool for investors and businesses looking to gain a competitive edge in the stock market.

Improved Collaboration: Power BI facilitates collaboration among team members by allowing them to share dashboards, reports, and insights. This enables multiple stakeholders to work together, analyze stock movements collectively, and make informed decisions.

Advanced Analytics: Power BI offers advanced analytics capabilities, such as predictive modeling and forecasting, which can help investors and businesses anticipate future stock movements. By leveraging these features, users can make data-driven predictions and take proactive measures to maximize their returns.

What is the formula for spend analysis?

There isn’t a single formula for spend analysis, as it involves various calculations and metrics depending on the specific goals and objectives of the analysis. However, some common formulas and metrics used in spend analysis include:

• Spend Analysis Ratio: Total spend on a category or supplier / Total spend
• Price Variance: (Current Price – Previous Price) / Previous Price
• Savings Calculation: Previous Spend – Current Spend
• Supplier Performance: Supplier Quality + On-Time Delivery + Cost Competitiveness
• Sourcing Savings: (Current Supplier Cost – New Supplier Cost) / Current Supplier Cost

The choice of formula depends on what insights you want to gain from your spend analysis and the data available.

What is ABC analysis in spend analysis?

ABC analysis, in the context of spend analysis, is a method of categorizing items or suppliers based on their importance to an organization. It helps prioritize items or suppliers for more focused analysis and management. The categories in ABC analysis typically include:

• A Category: High-value items or suppliers that represent a significant portion of spending and require close monitoring and management.
• B Category: Items or suppliers of moderate importance that require regular attention but not as much as A-category items or suppliers.
• C Category: Low-value items or suppliers that make up the majority of transactions but have relatively low impact on spending.

ABC analysis enables organizations to allocate resources effectively, concentrate efforts on areas with the most significant impact, and optimize their procurement strategies accordingly.

How can organizations improve supplier performance through spend analysis?

Improving supplier performance through spend analysis involves:

• Supplier Evaluation: Use spend analysis data to assess supplier performance in terms of quality, delivery, and cost competitiveness.
• Supplier Collaboration: Collaborate with key suppliers to identify areas for improvement and negotiate mutually beneficial agreements.
• Supplier Development: Invest in supplier development programs to enhance their capabilities and performance.
• Diversification: Identify and mitigate risks by diversifying the supplier base.
• Contract Management: Ensure that supplier contracts are clear, enforceable, and aligned with organizational goals.

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Corporate Spend sample for Power BI: Take a tour

The Corporate Spend built-in sample contains a report and semantic model that analyzes the planned versus actual costs of an IT department. This comparison helps you understand how well the company planned for the year. You can investigate areas with huge deviations from the plan. The company in this example goes through a yearly planning cycle. Quarterly, it produces a new latest estimate to help analyze changes in IT spend over the fiscal year.

This sample is part of a series that shows how you can use Power BI with business-oriented data, reports, and dashboards. The company obviEnce created samples using real, anonymized data. The data is available as a built-in sample in the Power BI service and a .pbix Power BI Desktop file. For more information, see Samples for Power BI.

This tour explores the Corporate Spend built-in sample in the Power BI service. Because the report experience is similar in Power BI Desktop, you can also follow along by using the sample .pbix file in Power BI Desktop.

Power BI Report

Bản report của học viên Việt Phương trên Power BI bao gồm 4 phần :

• Phân tích tổng quan chi tiêu dự đoán và chi tiêu thực tế của công ty trong 1 năm.
• Phân tích sự khác biệt giữa kết quả thực tế và kết quả kỳ vọng theo tháng.
• Đánh giá sự chi tiêu của công ty qua các tháng.
• Phân tích sự khác biệt trong chi tiêu của công ty vào từng quốc gia.

Dưới đây là bản report trên Power BI của học viên:

Exploring the Stock Movement Analysis Dashboard in Power BI

Power BI allows users to create customized dashboards to monitor and analyze stock movement. A dashboard is a collection of visualizations, reports, and other components that provide an overview of the key metrics and trends in your stock data.

When exploring the stock movement analysis dashboard in Power BI, you can leverage a variety of visualizations, including line charts, candlestick charts, area charts, and more. These visualizations can help you identify patterns, trends, and correlations in your stock data, providing valuable insights for decision-making.

One of the key features of the stock movement analysis dashboard in Power BI is the ability to drill down into specific time periods or stock categories. This allows users to focus on specific areas of interest and gain a deeper understanding of the factors influencing stock movement.

In addition to visualizations, the stock movement analysis dashboard in Power BI also offers interactive filters and slicers. These filters allow users to dynamically adjust the data displayed in the dashboard, enabling them to explore different scenarios and analyze the impact of various factors on stock movement.

Mục tiêu bài tập

Việc thực hành bài tập Power BI cuối khoá sẽ giúp các học viên:

• Rèn luyện kỹ năng phân tích, trực quan hoá dữ liệu trên Power BI một cách chỉn chu.
• Rèn luyện khả năng thuyết trình với stakeholders.
• Trau dồi kinh nghiệm thực hành một project phân tích dữ liệu thực tế trong doanh nghiệp.
• Thêm Project vào Portfolio cho các vị trí Data Analyst, Business Analyst,…giúp nhà tuyển dụng đánh giá năng lực ứng viên dễ dàng hơn.

Tham khảo thêm Final Projects của các học viên Datapot tại đây

Tham gia group ôn thi PL-300/DA-100 tại: https://www.facebook.com/groups/da100vn

Chuỗi Video Hướng dẫn thực hành Lab và sử dụng các tài nguyên của Microsoft: https://www.youtube.com/c/Datapotvn/videos

Update tài nguyên từ Microsoft, DA-100 exam questions và exam topics tại Fanpage của Datapot: https://www.facebook.com/DatapotAnalytics/

Với các bạn mới bắt đầu tìm hiểu Power BI & mong muốn ứng dụng Power BI trong công việc, hãy tham khảo khóa học PL-300: Microsoft Power BI Data Analyst từ Datapot.

Được thiết kế và giảng dạy bởi các chuyên gia giàu kinh nghiệm làm việc và đào tạo trong ngành dữ liệu, được triển khai tại các doanh nghiệp như Unilever, SHB, MB Ageas Life,.., khóa học sẽ mang đến cho bạn những kiến thức và kỹ năng thực tiễn nhất.

CEO & Founder DatapotMicrosoft Solution Expert, Microsoft Certified Trainer

Procurement Analysis sample for Power BI: Take a tour

The Procurement Analysis built-in sample contains a dashboard, report, and semantic model that analyze a manufacturing company’s spending on vendors by category and location. In the sample, we explore:

• Who the top vendors are.
• What categories we spend the most on.
• Which vendors give us the highest discount and when.

This sample is part of a series that shows how you can use Power BI with business-oriented data, reports, and dashboards. The company obviEnce created this sample using real, anonymized data. The data is available in several formats: built-in sample in the Power BI service, .pbix Power BI Desktop file, or Excel workbook. See Samples for Power BI.

This tutorial explores the Procurement Analysis built-in sample in the Power BI service. Because the report experience is similar in Power BI Desktop and in the service, you can also follow along by using the sample .pbix file in Power BI Desktop.

Giới thiệu về Dataset

Bộ dữ liệu (dataset) về Procurement Analysis được lấy từ kho dataset của Obvience.com, là bộ dữ liệu giả định của một doanh nghiệp trong thời gian từ 2010 – 2014, bao gồm các dữ liệu về:

• Danh sách mặt hàng;
• Thông tin hoá đơn mua hàng;
• Danh sách nhà cung cấp;
• Ngày tháng giao dịch;
• Mệnh giá, đơn vị tiền tệ thanh toán;
• Khu vực chi tiêu mua hàng.

Spend Analytics Visualization Tools

When working on a spend analysis, it helps to visualize the KPIs and metrics generated from the data. Several software applications can show the data in charts, tables, and graphs for faster understanding.

Using Spreadsheets

Spreadsheets are ubiquitous tools–almost everyone has them and knows how to use them. Most companies provide business software with spreadsheet applications to every employee. Thus many people usually consider spreadsheets to be ‘free.’

Spreadsheets are capable of doing advanced pivot tables and cross-tabulation reports. They can also show the information in a variety of line, bar, and pie charts. Yet, there are several areas of concern when using spreadsheets for Spend Analysis.

Common Concerns When Using Spreadsheets for Spend Analytics:

• Spreadsheets are error-prone. Studies by the University of Hawaii and Dartmouth College show that errors appear in 90% of spreadsheets and 1.7% of formulas. Many well-known corporations have made billion-dollar financial mistakes due to spreadsheet errors.
• Programming costs are high. Turning the data into pivot tables and charts requires a team of super users and procurement professionals. Even with a spreadsheet superhero, programming the formulas and creating tables and graphs takes a long time. The spreadsheet software may be free, but the team’s time isn’t.
• Editability and sharing can cause security and revision issues. Spend analytics should be shared to get the most out of them. Employees copy them onto their laptops and begin making edits to see the data they want in the way they want it. The original spreadsheet could get overwritten if protections are not in place. Also, a laptop with a spreadsheet copy could get stolen, putting your confidential data at a security risk.

Using Business Intelligence (BI) Tools

Business Intelligence tools have been around for over 40 years. Still, today’s computing power and graphics engines make them significantly more powerful.

Like spreadsheets, creating BI dashboards to display the KPIs and metrics will take an experienced BI programmer. Programmers and procurement professionals will have to work together to build a variety of views needed. Business intelligence tools were designed to generate complex graphs and charts, unlike spreadsheets. These elements can be saved as templates for future use.

Large companies that already invested in BI software and skilled programmers can expand their use to sharing procurement data. Organizations that regularly use BI for their operation metrics can combine that data and the spend data to uncover even more.

Business Intelligence visualization requires accurate, granular spend data and a method to get it. When done ‘by hand,’ the data preparation process involves many people and a long time. Business rules can support the process, though they usually only cover 20% of the data.

Using a Procurement Suite

Procurement Suites have integrated applications to handle lots of different procurement areas. These areas range from contract management to PR/PO processing to reverse auctions and expense management.

These are often reasonable general procurement solutions. However, these suites were not conceived as a whole. They usually expand by building new functionality or integrating technology from acquired companies. Suites often stay strongest in their core area. The Spend Analytics module may not have the simple interface of spreadsheets, the visual power of BI solutions, or the AI and advanced algorithms of analytics specific solutions.

Using a Spend Analytics Specific Solution

Strategic Procurement professionals know their team needs accurate, granular, high-quality data to analyze. Clean, deep data yields meaningful KPIs and metrics. They allow the procurement team to find more savings, to forecast future conditions, and to improve the sourcing process. Hence, spend analytics solutions apply serious engineering efforts to produce outstanding data.

Artificial Intelligence (AI) in Procurement

All the above solutions use business rules to help sort and categorize data. Better software also uses artificial intelligence (AI) to increase the processing speed and to improve accuracy. Natural Language Processing (NLP) deals with data that involve human language. Consolidating data from different sources becomes easier when NLP can identify all the versions of a supplier’s name during normalization.

Machine Learning (ML) allows a model to ‘train’ on a data set and bring the learnings to process a new data set. These trained algorithms can process and categorize data much more rapidly. What takes humans months takes the ML algorithms only days to complete. Software as a service (SaaS) delivery models provide faster computing power and more storage allowing greater use of AI in procurement.

These SaaS solutions are using AI to expand from reports and visualization into forecasts and predictions. Spend analysis can become a frequent procurement tool thanks to the improvements in the analytics software. Eventually, it will become a continuous process rather than a discrete activity.

Procurement Reports and Dashboards

Displaying the analytics requires a graphing library in the code. Putting the right KPIs and metrics for a use case on the same dashboard requires procurement expertise. Most spend analytics software has a few out-of-the-box reports and dashboards. Most systems provide configuration, customization, or creation of dashboards, depending on your needs. What you can do and see right away depends on the software solution’s capabilities.

Create a Corporate Spend dashboard

A Power BI dashboard is a single page containing visualizations that can come from one or more reports, and each report is based on one semantic model. You can also generate visualizations on the dashboard by using the Q&A Ask a question about your data feature to explore the data associated with a report. Think of a dashboard as an entryway into the underlying reports and semantic models. Select a visualization to take you to the report that was used to create it.

To create a dashboard in the Power BI service:

1. Open a report by selecting it in a workspace.

2. Hover over a visual and then select Pin visual.

   Or, to add all of the visuals to a dashboard, from the report menu, select … (More options) > Pin to a dashboard.

3. In Pin to dashboard, select New Dashboard and enter a name for your dashboard.

   You can add visuals to an existing dashboard to show visualizations from different reports.

4. Then select Pin Live.

Your new dashboard now appears in My workspace.

For more information, see Introduction to dashboards for Power BI designers.

Overview

The Purchase spend analysis Power BI content was designed to help purchasing managers and managers who are responsible for budgets keep track of purchase spending. Managers can analyze purchase spending in the following ways:

• Year-to-date purchase (by vendor group and individual vendors, procurement category and individual products, and vendor location)
• Year-over-year purchase change (by vendor group and procurement category)

The content uses purchase transactional data, and provides both an aggregate view of the company-wide purchase figures and a breakdown of purchase spending by vendor and product. Reports highlight changes in purchase spending over time. Therefore, the reports can be used to alert managers about positive and negative spending trends for individual vendors and products. Additionally, charts show purchase spending for different procurement categories and vendor groups. Therefore, category and regional managers can use the charts to help identify changes in spending behavior.

Explore the report

To open the Corporate Spend report, go to your workspace and select Corporate Spend.

A report can contain several pages with different visualizations. You can look at and interact with all the visualizations.

You can edit current visualizations and create your own visualizations that use the semantic model for this sample. This environment is a safe one to play in, because you can choose not to save your changes. But if you do save them, you can always return to the Learning center for a new copy of this sample.

Select Edit in the Power BI header bar to explore in the editing view:

• See how the pages are made, the fields in each chart, and the filters on the pages.
• Add pages and charts, based on the same data.
• Change the visualization type for each chart.
• Pin charts of interest to your dashboard.

Save or discard your changes.

IT Spend Trend page

This section describes the visuals from the IT Spend Trend section of the sample report.

1. To see data for all regions, select All regions from Select Sales Region.

   All the visualizations on the page reflect this selection. The Actual and Plan by IT Area and Actual by Period and Business Area visualizations show data from all regions.

2. Select Aus and NZ from Select Sales Region, and then observe the Actual and Plan by IT Area chart.

3. Now select USA. You can compare actual and planned spend for different selections.

Learn about the decomposition tree

Use the decomposition tree visualization, or decomp tree, to visualize data across multiple dimensions. You can aggregate data and drill down into your dimensions in any order. This tool is valuable for improvised exploration and conducting root cause analysis.

There’s a decomp tree in the IT Spend Trend page of the Corporate Spend sample. Open the report to experiment with the visualization.

1. For Select Sales Region, select All to query data from all regions.

2. Select the X next to Period and IT Area to remove those branches.

3. Next to Var Plan, select the plus sign, then select Sales Region.

   The decomp tree shows the six regions as branches.

4. Now select the plus sign next to Europe and then select IT Area.

5. You can follow the branches down for the sales region you select. You can expand any of the branches in IT Area for a different data type.

6. Select the X next to IT Area and Sales Region to remove those branches.

7. Next to Var Plan, select the plus sign, then select High value.

   The visualization shows Var Plan broken down by IT Area. The High value selection considers all available fields and determines which one to drill into to get the highest value of the measure being analyzed.

8. Next to Infrastructure, select the plus sign, then select Low value. This option gets the lowest value for the measure being analyzed, in this example, IT Sub Area.

For more information, see Create and view decomposition tree visuals in Power BI.

Plan Variance Analysis page

Open the report and select the Plan Variance Analysis page from the Pages column. For Select Sales Region, select All.

The Var Plan by Business Area shows the variance for all regions.

Below that visualization, the Var Plan % by Business Area is presented as a table of values. If you want to view it as a visualization parallel to the one above it, edit the report.

1. In the menu bar, select Edit.

2. Select the table then, under Visualizations, select the Stacked bar chart.

   Visualizations offers many options to display your data.

3. Select Reading view to exit the Edit mode and save your changes.

Customize tooltips

Power BI report visualizations display details about elements when you hover over them. For instance, open the Corporate Spend report and hover over a region in the map.

To see and edit tooltips:

1. Select Edit in the Power BI report bar to enter Edit mode.

2. Select the map visualization and, if necessary, expand Visualizations. Scroll down to see the Tooltips value.

3. You can change of add data fields to the tooltip. Drag a value from the Data pane to the Tooltip.

4. Select Reading view to leave Edit mode. Save your changes when prompted.

Now hover over a region again to see the value that you added.

For more information about tooltips, see Customize tooltips in Power BI.

Use hidden pages as tooltips

Power BI also supports a report page as a tooltip. To see an example, open the Corporate Spend report, select the IT Spend Trend page, and hover over Actual and Plan IT Area.

The displayed tooltip is a hidden report page. To see it, select Edit to enter Edit mode, then select the Tooltip tab.

You can create and edit this report page here. As a hidden page, it doesn’t appear with the other pages in the report. Add as many visualizations to this page as you want. Remember that, as a tooltip, a large page covers up a lot of space in your report view.

For more information, see Create tooltips based on report pages.

Plan Variance Analysis page

1. Select the Plan Variance Analysis page.

2. In the Var Plan and Var Plan % by Business Area chart on the left, select the Infrastructure column to highlight infrastructure business area values in the rest of the page.

   Notice in the Var plan % by Month and Business Area chart that the infrastructure business area started a positive variance in February. Also, notice how the variance-to-plan value for that business area varies by country or region, as compared to all other business areas.

3. Use the IT Area and IT Sub Area slicers on the right to filter the values in the rest of the page and to explore the data.

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Trước khi kết thúc mỗi khóa học tại Datapot, các học viên đều có cơ hội làm bài tập dự án. Việc làm dự án sẽ giúp học viên được thực hành giải quyết một vấn đề cụ thể do học viên tự lựa chọn và nhận được lời nhận xét từ ban giám khảo là những giảng viên, chuyên gia trong ngành Dữ liệu.

Dưới đây là bài tập dự án trong khóa học Power BI của học viên Dương Thị Phượng Yến.

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Microsoft’s Power BI is a common business intelligence tool used by business analysts and professionals. Learn more about this important tool today.

Microsoft Power BI is a data visualization and reporting platform that is used by businesses and professionals every day. While the platform is commonly used by business analysts, it is also designed to be easily accessible for those without any specialized data knowledge.

In this article, you’ll learn more about Power BI, what modern businesses use it for, and the professionals who typically work with it. Toward the end, you’ll also explore some alternatives and explore online specializations and guided projects that can help you get started with this important business intelligence tool.

Microsoft Power BI is a data visualization platform used primarily for business intelligence purposes. Designed to be used by business professionals with varying levels of data knowledge, Power BI’s dashboard is capable of reporting and visualizing data in a wide range of different styles, including graphs, maps, charts, scatter plots, and more. Power BI’s “AI Insights” functionality, meanwhile, uses artificial intelligence to find insights within data sets for users.

Power BI itself is composed of several interrelated applications: Power BI Desktop, Pro, Premium, Mobile, Embedded, and Report Server. While some of these applications are free-to-use, paid subscriptions to the pro and premium versions provide greater analytics capabilities.

Power BI is also a part of Microsoft’s Power Platform, which includes Power Apps, Power Pages, Power Automate, and Power Virtual Agents. Created as “low-code tools,” these applications help businesses analyze and visualize data, design business solutions, automate processes, and create no-code chatbots.

Read more: 5 Business Intelligence Tools You Need to Know

Whether you’re a data pro or are just entering the business world, Power BI is designed to empower you with data-driven insights. Some of the most common uses for the platform include:

Creating reports and dashboards that present data sets in multiple ways using visuals

Connecting various data sources, such as Excel sheets, onsite data warehouses, and cloud-based data storage, and then transforming them into business insights

Turning data into a wide range of different visuals, including pie charts, decomposition trees, gauge charts, KPIs, combo charts, bar and column charts, and ribbon charts – among many other options

Providing company-wide access to data, data visualization tools, and insights in order to create a data-driven work culture

Power BI users aren’t limited to data professionals, such as data scientists or data engineers, and can include a wide range of different business users. In fact, the platform is intentionally designed so non-technical users can easily create reports, manipulate data, and perform in-depth data analysis operations.

Nonetheless, some of the most common analyst positions that use the platform on a daily basis include the following:

As data becomes more and more important to the daily functioning of the goods and services that businesses provide, so too do business intelligence platforms capable of turning that data into insights, reports, and interactive visualizations.

For example, a university attempting to optimize the efficiency of their buildings might set up a system (like a digital twin) to collect real-time data on critical building systems. Afterward, they might connect these data sources to Power BI and identify areas for improvement.

An advertising company, meanwhile, running a digital marketing campaign might monitor its effectiveness by connecting various data sources to Power Bi and generating a dashboard that highlights key figures. Here, marketers would be able to better understand what marketing channels are best for reaching their target market.

Want to learn more about Power BI but aren’t sure where to start? Coursera Guided Projects offer step-by-step instructions on how to use the platform. In the project-based, interactive course Getting Started with Power BI Desktop, you’ll learn the basics of the platform in just two hours.

In the free Guided Project, Prepare, Clean, Transform, and Load Data using Power BI, you’ll learn practical ways for data cleaning and transformation on the platform.

While Microsoft’s Power BI is one of the most popular business intelligence platforms, it’s not the only one out there. As you’re exploring BI solutions for your workplace or future career, then, you might also consider exploring some common alternatives to Power BI, such as:

Tableau

Domo

Yellowfin

Qlink Sense

SAP Business Intelligence

Data empowers modern businesses, equipping them with actionable insights that facilitate strategic decision making. Prepare for a career in business analytics by taking a cost-effective, online specialization on Coursera.

In Wharton’s Business Analytics Specialization, you’ll learn how data analysts describe, predict, and inform business decisions in the specific areas of marketing, human resources, finance, and operations, while also developing basic data literacy and an analytic mindset that will help you make strategic decisions based on data. Best of all, the specialization is designed for all business professionals, including those without any prior analytics experience.

Through Google’s Data Analytics Professional Certificate, meanwhile, you’ll learn how to visualize and present data findings in dashboards, presentations and commonly used visualization platforms.

Editorial Team

Coursera’s editorial team is comprised of highly experienced professional editors, writers, and fact…

This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

How to Use Power BI for Stock Movement Analysis: A Step-by-Step Guide

How to Use Power BI for Stock Movement Analysis: A Step-by-Step Guide

Stock movement analysis is a crucial aspect of financial analysis and decision-making for investors, traders, and businesses. By understanding the factors that influence stock prices, investors can make informed decisions and maximize their profits. In this comprehensive guide, we will explore how Power BI, a powerful data visualization tool, can be used for stock movement analysis. We will cover everything from the importance of stock movement analysis to setting up Power BI, analyzing historical stock data, applying filters and slicers, leveraging DAX formulas, and integrating external data sources. Let’s dive in!

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