If your search for “business intelligence vs. reporting” led you to this post amidst the large volume of online results, you’re likely acquainted with the numerous interpretations of these two practices. Business intelligence (BI) has become a buzzword with various meanings, depending on who you consult. But now that you’re here, let’s get straight to the point: It’s pivotal for Microsoft Dynamics users to comprehend the difference between business intelligence and reporting, and this article is dedicated to clarifying that distinction.
If you do not clearly identify the differences and define the two practices, there is a chance you will end up using the wrong tools for the job. Not only will this mean a lot of wasted time on your part, but you are also in serious danger of obtaining and using the wrong data. This can be devastating to your business as there are numerous consequences including making business decisions from a corrupt set of data to auditing implications. Learn to avoid the risks by letting us lay out the true differences between business intelligence and reporting once and for all.
Conceptual Application for Reporting vs. Business Intelligence
First things first: the phrase “business intelligence vs. reporting” is misleading as one doesn’t exclude the other. In fact, both are paramount to business operations and both are required for an enterprise to operate competitively.
Reporting is an insight into the past and/or the present.
Reports tend to shed light on a specific operation or dataset for a set period (monthly sales, daily customer orders, weekly open AP, etc.). Reports may also initiate short-term action. For example, a daily report with information on all orders and their final destination will enable employees to accomplish accurate and prompt delivery. To boil it down: Reports are micro-oriented. They are designed for operational staff like accountants, AP clerks, fulfillment managers, or salespeople to time-optimize the required actions needed in the business.
Business intelligence (BI) is about gaining insight into the past to change or improve the future.
Also often known as “analytics,” BI has a more extensive database that might even range over multiple data collection systems such as CRM and GP. It identifies trends for making informed strategic business decisions that will impact overall performance in the entire operation. Worded differently: business intelligence is macro-oriented. Where the Daily Shipping Report will inform on the current situation, BI provides a Shipping Performance Over Time, by region, carrier, warehouse, and by product for various operations, destinations, or carriers used. This data can highlight where changes are necessary, or where efforts and resources are wasted.
BI brings another important characteristic to the table: governed truths. It’s necessary to universally define goals and performance equations through KPIs and metrics that are calculated in the BI environment indefinitely. BI ensures that everyone is always on the same page and that employees work towards the same clear goals collectively identified from information that is universally assumed to be correct, i.e., there will be no variations and no discussion on which numbers are more correct than others. Consequently, accurate and consistent data will give your organization a head start.
Technical Application for Reporting vs. Business Intelligence
Now that we have distinguished reporting from business intelligence, in theory, we can take a look at how the two differ in technical application. This is very important and understanding the framework behind data-output will save you from choosing the wrong tool and wasting your time. It will also mitigate the risk of getting inaccurate data in your financial statements, operational reports, or analytical dashboards.
Reporting Infrastructure
As mentioned earlier, reporting is generally a necessary transactional-based exercise between two parties. Most reporting tools are therefore based on a two-dimensional database structure of tables and fields. Often, Microsoft Dynamics NAV and GP database users have upwards of 1500 tables ranging from Customer, Accounts Payables, Inventory, and G/L areas, in addition to both master data tables (customer contact records, chart of accounts, item cards) and transactional data (sales orders, invoices, etc.). Not to mention that reporting typically draws and refreshes data in real time from the live production database.
If that sounds like an overwhelming amount of information to navigate, that’s because it is – more often than not. However, reporting is certainly necessary and optimal for many financial and operational tasks, as it lets you gain insight into what is happening right at this moment. This means you can look up particular, detailed transactions that compose the numbers the report reveals.
The good news is that it is easy to simplify and organize reporting like this with third-party reporting add-ons built for Microsoft Dynamics, such as Jet Reports. The software unscrambles data from the original source and presents it in a familiar Excel integration for formatting, report-building wizards, drill down/drill back, and easy access.
When we consider the technical applications of reporting tools, it is important to recognize the limitations; let’s explore a few. Firstly, reporting does not work well with large volumes of data, as there is a big risk of inconsistency and discontinuity in the final numbers. For example, reporting on performance over a longer period from the live production database will be an insurmountable task because there will be far too many records to manage manually. Also, analytics reflecting trends and summaries by broad, varying breakdowns or company-wide goals and metrics will have a high risk of errors because of the unlimited approaches to combining and calculating the data.
This can happen with all data points calculated after the fact. An example is the Cost of Goods Sold (COGs), which does not exist in the database itself but is calculated based on desired varying inputs such as purchases, supplies, labor, and overhead. As there is no one way of calculating this data point, the outcome can affect everything between summary income statements and sales analysis. When no one is conclusively right, everyone is wrong, and this is why reporting tools should not be used for attempted analysis.
The COGs issue is just one example of what can happen when using reporting tools to do strategic data gathering and analysis. Departments and individual people treat metrics, KPIs, and where they pull their data from differently, which is why business intelligence is a key tool to have under your belt.
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Business intelligence provides you with a platform that automatically takes raw two-dimensional live data, defines what pieces of it are relevant, and then structures it and subjects it to optimize for fast analysis. To do this, the common practice is to use a data warehouse, which is an entirely separate environment from your production database.
A data warehouse is a super-organized version of your Dynamics database; it outperforms a production database environment in terms of containing data as it can combine data from external sources, such as CRM, a legacy ERP, or an industry-specific system, into one, convenient place. In contrast to the Microsoft Dynamics database, which is built for entering data, a data warehouse is solely built for extracting data points. It will consolidate data and eliminate clutter in your output.
Although this is very valuable for a BI initiative, the data output is still two-dimensional and does not contain analyzable KPIs or calculated numbers. This is where OLAP cubes come into play. When they are built from your data warehouse, cubes provide dimensionalized combinations of the data as they slice and dice it beforehand. They will also allow you to save rules and pre-calculated KPIs, such as your COGs or Gross Margin, so results are available to portray and break down promptly on any other data point desired – and the numbers are always consistent across users. For example, any employee can request Contribution Margin KPI, by product, time, region, reseller, or any combination thereof, and receive the same, accurate data instantly.
The data warehouse will not produce the data, as it is separate from your live, production data sources. Therefore, reports, dashboards, and analyses that come from the data warehouse and OLAP cubes will not be “real-time,” and it should not be. You can choose at which intervals the data warehouse needs to sync with Microsoft Dynamics and other connected databases, ensuring it will happen when it’s most convenient for you. Syncing every night is usual, so it doesn’t disrupt any other systems during working hours. Another popular approach is refreshing smaller parts more often, referred to as incremental loading or refresh, as the disruption is not as pronounced and at the same time, your information is more up-to-date.
Reporting and business intelligence are both essential and serve different purposes for your business. Reporting is a basic but extremely valuable tool for day-to-day progress in operations, where business intelligence provides a more holistic insight into your data to help understand and analyze it better for competitive advantage.
A useful analogy to summarize the difference between business intelligence and reporting can be navigating your way from A to B. Reporting is your map with all the data points; it is helpful for you to see the current landscape around you, but the map itself won’t help you understand which route is optimal. This is where BI works its magic, as it represents the GPS that uses the map as a base, and calculates the best way to get to point B, based on a combination of rules (do you want to avoid tolls?), traffic conditions, speed limits, and other dimensional data.
Consider almost any industry analyst or trend report such as technologyadvice.com or Gartner, and there is no doubt that BI is going to separate the winners from the losers in their markets. In other words, business intelligence isn’t a “nice to have” anymore, it has become a necessary competitive survival tool. For this reason, business intelligence technology is quickly evolving and specializing. Small to medium-sized businesses especially can rapidly see the return on the initial investment today.
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Tigunia offers complete BI solutions built for Microsoft Dynamics including pre-built data warehouses and dashboards so you can start analyzing your data quickly and easily. Our BI offerings are designed to bypass the costly and protracted process of constructing a data warehouse, which can be time-intensive and yield less-than-optimal outcomes. With Tigunia, you can unlock the potential of business intelligence in just a few hours, leveraging the full capabilities of analytics, dashboards, and BI, including the integration of Power BI.
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