Business Intelligence vs Data Analytics for Professional Services

Business Intelligence vs Data Analytics: A Growing Market

In delivering projects on time and on budget, every time, understanding and interpreting data is critical to a professional services organization’s success. However, as interest and adoption in data and analytics has grown, a multitude of new terms and concepts have emerged making it difficult to keep up with various product offerings, solutions, and even the language around data. The market and information surrounding business intelligence vs data analytics, and even smarter professional services automation solutions, continues to grow at a high rate. At Projector, we find it helpful to distinguish between a few of these terms to emphasize how they impact everything from finance and accounting to project service and delivery.

First, let’s start with business intelligence.

What is Project Management Business Intelligence?

Business intelligence (BI) is really an umbrella term that encompasses all of the data and technologies used to derive insights from business operations and practices. You might use project management BI to examine your accounting data to look for errors or discrepancies in invoices or other financial information to mitigate risk or properly reconcile your books. Commonly, BI is used on the sales and marketing side as well to gauge the efficacy of marketing campaigns, examine existing sales pipeline and opportunities versus close rates.

On the product side, we use BI tools to measure product rollouts, adoptions, and insights into user behavior. We’ve also developed a Power BI project management solution for professional services organizations called Projector BI. The key piece to understand with project management business intelligence is that it can be adapted to any data you have that provides insight into your operations or business objectives.

See a sample of Projector BI to discover the insights a BI tool can provide.

What is the Difference Between Business Intelligence vs Data Analytics?

The next logical question is “What is the difference between business intelligence vs data analytics?” Both business intelligence and analytics collect data, provide insights, and represent your data visually with charts, dashboards, graphs and tables. The most commonly accepted difference between the two terms is that business intelligence focuses on past data to address the present. What can be done now to improve business operations and service delivery today?

Analytics tends to be more future focused. With analytics, the focus tends to be on predictions for the future to answer questions like “What markets can we grow into? or Where should we invest in innovation to increase revenue?”

Business Intelligence vs. Data Analytics

So where should you focus your attention when it comes to business intelligence vs data analytics? Typically the answer would be both for critical visibility into all aspects of your professional services organization and a firm grasp on your operational processes and efficiencies. The question should be less about business intelligence vs data analytics, and more about what your needs are surrounding your business data, objectives, and resources to develop a successful strategy.

However, when thinking about analytics, we find it helpful to break analytics down further into three distinct categories.

What are Three Types of Project Management Analytics?

We use the commonly accepted language of descriptive, predictive, and prescriptive analytics.

  • Descriptive Analytics

    Descriptive analytics looks at data in the present to describe what is happening in real time. A good example would be a chart showing hours billed to a project to date versus budget and milestones. You can use that descriptive data in real time to adjust resources to align to successful delivery of your project. Unlike business intelligence, which is looking at past data to inform business operations, descriptive analytics is concerned with what is happening today and painting an informed picture.

  • Predictive Analytics

    Predictive analytics takes this data a step forward into the future. Using that same example of project hours to date versus budget and milestones, predictive analytics makes predictions about where the project will land based on the current state. It would include predictions like the estimated completion date, number of hours expected to deliver, and estimated completion of future milestones. Predictive analytics in project management can also be applied at a higher level to all projects and even future opportunities to assess future growth, revenue, and capacity to deliver.

  • Prescriptive Analytics

    Prescriptive analytics uses data to make suggestions about what to do in order to meet your objectives. Rather than simply predict outcomes on your project, prescriptive analytics is often used for nudging behavior that has proven to be impactful to goals. For example, if your project was behind schedule, but below budget, prescriptive analytics may suggest adding certain resources or even swapping out resources to increase your likelihood of successful delivery.

business intelligence vs data analytics

What are the Benefits of Business Intelligence and Data Analytics in Project Management?

Parallels are often drawn between data and gold. Gold is incredibly valuable, but most of it is simply sitting underground without purpose. For professional services organizations, there is immense value in the data that sits underneath daily business operations. Projector can use this treasure trove of valuable data to create an entire lifecycle of your business. Your customer relationship management (CRM) software begins that journey in creating leads, opportunities, and can be leveraged for forecasting resources needed for your business at an early stage.

As your prospects turn into commitments, data on your clients’ needs, goals, and budgets is necessary to finding best fit resources within your organization for successful delivery, which is paramount to ongoing revenue growth and client satisfaction. It doesn’t stop there. We work with clients to combine their back-office operations, including finance and accounting, to optimize the engine of your services business for growth and efficiency. We have over a decade of experience working with clients to harness the power of data across your organization and systems to attract the right projects, assign the best fit resources, deliver quality work, and streamline your business operations.

Read on for more on the benefits of project management analytics for services organizations and how they help with project and budget forecasting. Or take a look at our interactive case study on forecasting revenue. And if you’re serious about driving success with project management business intelligence and analytics, read our e-book about how PSA (professional services automation) can deliver the visibility, efficiency and BI to drive your services business.

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Discover how Professional Services Automation can unleash the power of Business Analytics to fuel growth.

Frequently Asked Questions About Business Intelligence vs Data Analytics

What is project management business intelligence?

Business intelligence (BI) is really an umbrella term that encompasses all of the data and technologies used to derive insights from business operations and practices. The key piece to understand with project management business intelligence is that it can be adapted to any data you have that provides insight in your service operations or business objectives.

What is the difference between business intelligence vs data analytics?

While both business intelligence and data analytics collect data, provide insights, and represent data visually, business intelligence focuses on past data to address the present. Analytics tends to be more future focused.

What are three types of business analytics for project management?

Three common types of business analytics for project management in include:

1. Descriptive Analytics: Looks at data in the present to describe what’s happening in real time.
2. Predictive Analytics: Takes this data a step forward in to the future.
3. Prescriptive Analytics: Uses data to make suggestions about what to do in order to meet objectives.

What are the benefits of benefits of predictive analytics in project management?

Predictive analytics can make predictions about where a project will land based on its current state, including an estimate of estimated completion date and expected number of hours to deliver. At a higher level, benefits include having the capability to asses capacity to deliver your projects successfully, paving the way for revenue growth and improved client satisfaction.

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