Implementing analytics software has been a major initiative for companies undergoing digital transformation, and the main subsection of analytics tools deployed in companies are business intelligence (BI) tools. These BI tools help to provide visibility into a company’s data. By being able to visualize and understand business data, employees can make more informed decisions and impact the company in a positive way. With the amount of data accessible to businesses today, it is a near necessity that they implement some type of BI software to better understand and act on that data.
Key Benefits of Business Intelligence Software
In today’s big data world, every company is sitting on an enormous amount of data. Inside lies insights that can make or break company processes and performance. The question should not be why use business intelligence software, but why not use business intelligence software? There are seemingly infinite insights a business can pull from their data, but here are three important reasons to use business intelligence software.
Data-Driven Decision-Making — A key component to digital transformation is to become a data-driven organization. By using data to drive every decision the business makes, the company can optimize and achieve its fullest potential. This concept should be instilled within every employee in the company, not just a few leadership members who make high-level decisions. Instead, companies should be leveraging analytics and business intelligence tools to understand all aspects of the business, including hiring forecasts, which marketing campaign should be used to target certain demographics, which sales prospects to target first, supply chain optimization, and many others. Each of these business aspects and the decisions made around them should first be vetted by using data and business intelligence software. Every manager and leader should be asking what data was used to determine each decision.
Measure and Understand Company Performance — Another main reason that businesses adopt business intelligence tools is for tracking and measurement of company goals. Data visualization tools are frequently used to track company key performance indicators in real time. Business intelligence platforms and self-service business intelligence software can be used to then determine why the business is either exceeding or falling short of those important company metrics. By developing a keen understanding of why the business is performing the way it is, adjustment and pivots can be made quickly and easily. So if a team is falling short of a goal, they can make up for it and get back on track. It is one thing to simply know where your sales numbers are or how your web traffic is performing, but it is another to dig into the reasons behind it and adapt based on what is successful and what is not.
Discover New Actionable Insights — BI tools combine data from a variety of sources, including accounting and enterprise resource planning (ERP) software, CRMs, marketing automation tools, and others. Data analysts can use this integrated data to find correlations between different departments and the actions they are taking to discover previously hidden insights. It’s possible that certain sales tactics are impacting the numbers for one specific product differently than they are for another. Analysts can discover this by comparing the list of closed accounts from their company CRM with products shipped in their ERP system. Because teams are generally siloed and using disparate software, these insights have traditionally been much more difficult to discover. However, by using business intelligence software properly, companies are at an advantage they never had in the past.
There are a number of different types of business intelligence (BI) solutions that have overlapping functionality but ultimately cater to a different user or provide unique services.
Business Intelligence Platforms — The most common type of BI tools are business intelligence platforms. BI platforms are comprehensive analytics tools that are used by data analysts and scientists. They often require a certain level of coding or data preparation knowledge. These solutions connect to databases, data warehouses, or big data distributions and offer analysts the ability to tinker with data to discover insights. Some BI platforms offer advanced analytics features, such as predictive analytics, big data analytics, and the ability to ingest unstructured data. Additionally, BI platforms may offer self-service functionality so that basic business users can use the tool, but at the core they are to be used by data and IT teams.
Self-Service Business Intelligence Software — For companies interested in promoting a data-driven culture, self-service business intelligence software is critical. Self-service business intelligence tools do not require coding knowledge, so business end users can take advantage of them. These solutions often provide drag-and-drop functionality for building dashboards, prebuilt templates for querying data, and maybe even natural language querying for data discovery. Similarly to BI platforms, these tools are used to build interactive dashboards for discovering actionable insights. This allows users like sales representatives, human resource managers, marketers, and other non-data team members to make data-driven decisions. This saves time for the user, administrator, and data team.
Embedded Business Intelligence Software — Some software may offer the ability to embed analytics functionality inside of other business applications. Often, these are the same vendors that offer BI platforms and self-service business intelligence software. They sell their proprietary business intelligence solutions by allowing developers to embed the technology inside other applications. Businesses may choose an embedded business intelligence product to promote user adoption. By placing the analytics inside regularly used software, companies can help to ensure employees are taking advantage of available data. These solutions provide self-service functionality so that average business end users can take advantage of data for improved decision making.
Data Visualization Software — If a business is interested in simply tracking key performance indicators (KPIs) and other important metrics, they may opt to use a data visualization software. These products allow users to build dashboards to track company goals and metrics in real time. However, they do not allow users to drill down into the data to discover deeper insights. By understanding where a business or team sits with certain company goals and KPIs, they can make efforts in specific areas to achieve said goals. These solutions allow for multiple KPI dashboards, so each team can set up visualizations for their own goals. These tools can consume data from a variety of sources, just like all other business intelligence tools, such as databases and business applications.
Location Intelligence Software — Often called spatial intelligence, location intelligence software is a subset of business analytics that provides insights based on map and spatial data. These tools help users determine relationships between the physical location of objects. In the same way a user can find patterns in financial or sales data with a BI platform, data analysts can use location intelligence tools to determine the ideal spot to open their next restaurant or place their next warehouse. These tools are often used separately from a business intelligence tool or even integrate with existing analytics tools.
In a data-driven organization, business intelligence (BI) tools should be adopted by a variety of departments for a wide range of purposes. BI software is most frequently used by data analysts and data scientists, but self-service BI tools, which are much easier for the average end user to adopt, can be used by sales, marketing, and operations teams. In reality, nearly every employee should be using analytics solutions at some point to truly become a data-driven company. While there are point solutions that provide analytics for very specific departmental purposes, such as marketing analytics software, sales analytics software, and HR analytics software among others, BI tools can offer the same functionality on a much broader level and allow for cross-departmental insights.
Data Analysts and Data Scientists — The main users of BI tools are data teams consisting of data analysts and data scientists. These employees are generally the power users of analytics tools, creating complex queries inside BI platforms to gather a deeper understanding of business critical data. These teams may also be tasked with building self-service dashboards to distribute to other teams. In smaller companies, these employees are most likely tasked with providing all data requests and working closely with the sales, marketing, and operations teams to help offer insights and optimize processes.
Sales Teams — Sales teams can use both self-service business intelligence tools and embedded business intelligence solutions to find insights into prospective accounts, sales performance, and pipeline forecasting, among many other use cases. Generally, the sales team members that use analytics on a daily basis are sales operations managers or sales data analysts. However, they are extremely useful for both sales managers and representatives. Managers can help keep tabs on the performance of each representative and maintain a clear picture of the potential pipeline. Additionally, sales teams can use data visualization software to track year-long goals and quotas to give the entire company visibility into high-level sales numbers. Ultimately, using BI tools in a sales team can help businesses optimize their sales processes to ensure they are bringing in the most revenue possible.
Marketing Teams — Marketing teams are constantly running different campaigns, whether they are email, digital advertising, or even billboard campaigns. BI tools are a great way for teams to track the performance of those campaigns in one central location. Data visualization solutions are a great way for marketing teams to track campaigns in real time, and by measuring the performance of each effort, teams can plan for future campaigns and forecast how much revenue they can attribute to said efforts. BI platforms can allow analysts to dig deeper into marketing efforts by segmenting customers based on a range of demographics to really understand which campaigns resonate with which segment of their customer base. This can help the marketing team make a targeted effort moving forward. Similarly to sales use cases, marketing teams can utilize BI software to help improve their bottom line and provide transparency and visibility into their overall performance.
Finance Teams — Accounting teams generally stick to the tools they are familiar with for budgeting and forecasting, but by blending financial data with sales, marketing, and other operations data, users can pull actionable insights that they were unable to see before. They can find these insights by using BI platforms to get an understanding about which factors impact the bottom line. Additionally, they can determine the right and wrong places to spend money. For example, if a specific advertising campaign was the cause for a revenue spike, then that was money well spent. If a specific product is yielding less profit than others based on the effort of the sales team, then finance teams can inform their sales leaders and adjust accordingly. The beauty of BI tools is that it does not just give insights into financial records, like accounting or corporate performance management software; instead it gives actionable insights into how all the other business factors impact profit and loss.
Operations and Supply Chain Teams — One potential data source for BI solutions is a company’s enterprise resource planning (ERP) system. These applications track everything from accounting to supply chain and distribution. By inputting supply chain data into a BI platform, supply chain managers can optimize a number of processes to save time and resources. For example, businesses can optimize inventory to ensure that they are not over- or underproducing. With location intelligence software, companies can determine the best location for their next warehouse. BI platforms can help optimize distribution routes and ensure service-level agreements (SLAs) are hit on time. Additionally, data visualization software can help warehouse workers track their daily goals to ensure all operations are running smoothly. All of these optimizations can help businesses stay on track and achieve higher company-wide goals.
Need for Skilled Employees — Business intelligence software is not necessarily simple. Often, these tools require a dedicated administrator to help implement the solution and assist others with adoption. However, there is a definite shortage of skilled data scientists and analysts that are equipped to set up such solutions. Additionally, those same data scientists will be tasked with deriving the actionable insights from within the data. Without people skilled in these areas, these tools are not nearly effective. Even the self-service business intelligence tools, which are to be used by the average business user, require someone to help deploy them. Companies can turn to vendor support teams or third-party consultants to assist if they are unable to bring someone in-house.
Data Organization — Business intelligence solutions are only as good as the data that they consume. To get the most of the tool, that data needs to be organized. This means that databases need to be set up correctly and integrated properly. This may require building a data warehouse, which can store data from a variety of applications and databases in a central location. Businesses may need to purchase a dedicated data preparation software tool as well to ensure that data is joined and clean for the business intelligence solution to consume in the right way. This often requires a skilled data analyst, IT employee, or an outside consultant to help ensure data quality is at its finest for easy analysis.
User Adoption – It is not always easy to transform a business into a data-driven company. Particularly at older companies that have done things the same way for years, it is not simple to force analytics tools upon employees, especially if there are ways for them to avoid it. If there are other options, such as spreadsheets or existing tools that employees can use instead of business intelligence software, they will most likely go that route. However, if managers and leaders ensure that business intelligence tools are a necessity in an employee’s day to day, then adoption rates will increase. It is one thing to implement business intelligence tools in an attempt to reach digital transformation, but unless users are embracing the software, then they are not truly achieving digital transformation.
Outside of the business intelligence umbrella, there are a number of analytics and related solutions that interact with business intelligence tools.
Big Data Analytics Software — Big data analytics software have similar functionality to business intelligence platforms. However, they can consume large, unstructured data sets from big data clusters. These products require a good deal of technical knowledge to query the data from the file systems the data is stored within. These products connect to Hadoop or proprietary Hadoop distributions. They still offer analysts the ability to visualize and drill into data to pull out actionable insights.
Text Analysis Software — Text analysis software allows users to visualize data from unstructured text data sets. These tools often use natural language processing to pull out sentiment analysis, syntax parsing, part-of-speech tagging, and entity classification. These tools are often used by data teams and analysts. They can be used to gain insights from emails and phone transcripts, social media posts, or just general documents.
Predictive Analytics Software — Data scientists and machine learning developers may require predictive analytics software. These solutions allow users to perform data mining on historical data to determine future outcomes. With predictive analytics tools, analysts can build models and algorithms that use patterns and trends from past data to plan for future possibilities. These solutions are critical when forecasting, identifying potential risks, or finding unseen opportunities within the business.
Data Warehouse Software — Most companies have a large number of disparate data sources, so to best integrate all the data, they implement a data warehouse. Data warehouses can house data from multiple databases and business applications, which allows business intelligence tools to pull all company data from a single repository. This organization is critical to the quality of the data that is ingested by analytics software.
Data Preparation Software — Another key solution necessary for easy data analysis is a data preparation tool. These solutions allow users to discover, combine, clean, and enrich data for simple analysis. Data preparation tools are often used by IT or data analysts tasked with using business intelligence tools. Some business intelligence platforms offer data preparation features, but businesses with a wide range of data sources often opt for a dedicated preparation tool.
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