Business Intelligence, also known as BI for short, combines business analytics, data mining, data visualization, data tools and infrastructures to help organizations make strategic decisions. You hear the buzz all around. It sounds like all of your competitors have been doing BI for ages and you’re feeling a little anxious that you might be left behind. Well rest assured — not everyone has implemented BI just yet. In fact, based on my sample survey of distributors, manufacturers and logistics service providers less than 20% employ any BI worth mentioning.
But to ensure that we’re on the same page let’s focus on the most common business intelligence terms for logistics providers.
Basic Definitions of Common Business Intelligence Terms:
Business Intelligence (BI): In simple terms it is the accumulation, analysis, reporting, budgeting & presentation of your business data. The goal of utilizing business intelligence for your business is to improve your visibility of your organizational operations and financial status to better manage your business.
Key Performance Indicators (KPI): These are the ratios, formulas and calculations of data that shows the most important measurements to focus on in order to best run your company. Typically, each industry will have their own KPIs. But there are also some common KPIs across all industries such as: Revenues, Expenses, Net Income, Profitability, etc.
Dashboards: Similar to the dashboard from your car, imagine all of the dials and gauges as a graphical representation of your financial/operational data in an easy to understand format. Dashboards are used by executives to more easily keep their pulse on the corporate operations by quickly glancing at the KPIs shown on the dashboard. Usually, the data shown is summarized data. The detailed information will be found in the reports or via analysis of the data in the database via OLAP cubes.
Reporting: Most often there is financial reporting and operational reporting. Financial reporting adheres to reporting that is focused on the financial modules of an ERP system and operational reporting is reporting that is based on the operational processes of an organization. Consolidated financial reporting refers to the consolidated financial reporting across separate legal entities for the purposes of consolidating the financial amounts for the corporate entity of that company, as well as for the analysis of the financial data across legal entities for corporate executives.
Budgeting: Budgeting is setting up pre-allocated amounts for future revenues and expenses for your organization. Most companies will budget one year at a time. Some will budget for 3 years and some companies budget up to 5 years ahead. There are three common types to consider:
- Profit & Loss Budgeting (P&L): Budgeting only for categories as defined by your general ledger chart of accounts. This is the most common form of budgeting.
- CapEX Budgeting: Budgeting for Capital Expenses.
- Headcount Budgeting: Budgeting for labor expenses and employee salaries.
Forecasting: Forecasts are revisions to the finalized budget. i.e. You have a 2015 annual budget and your 2015-Q1 Forecast would be your revisions to the Q1 budget figures for the 2015 year. However, you would still have both your annual budget and your forecasts as finalized documents for reporting and comparison purposes.
- Sales Forecasting: Forecasting for projected sales revenue. Sales forecasts can be forecasted down to a product category, product, salesperson territory, salesperson, etc.
- Purchase Forecasting: Forecasting for projected purchases.
Data Warehousing (DW): Is the accumulation, cleansing and correlation of disparate data (i.e. from disparate data sources) into a single database to facilitate consolidated reporting, analysis, etc. The goal of a data warehouse is to take data from disparate systems that are possibly in disparate languages and create one uniform language with one uniform set of business logic.
For example, a manufacturer might be using Microsoft Dynamics GP as their financial system, a warehouse management system as their operation system, and they might have a home-grown project tracking system. None of these systems talk to each other and a customer in one system is in a different format than a customer in another system. The goal of a data warehouse project would be to combine the necessary data (depending on the goals for the DW project) from the three different systems, eliminate duplicate entries of data, eliminate “junk” data & correlate all of the data together so that (for example) there is only one “customer” in the data warehouse. As a result, it will be much easier for users to get consolidated reporting across those three systems. The phrase “one single version of the truth” is often alluded to regarding a data warehouse since it is supposed to give you one clean set of data across all of the systems you’re consolidating to report and perform analysis on.
Once the DW is built you can report from it, you can utilize it to assist with budgets/forecasts, you can create dashboards displaying KPIs from it, you can utilize OLAP cubes to “slice and dice” the data for analysis, etc.
Online Analytical Processing Cubes & Analysis (OLAP): In simple terms an OLAP cube is a data structure that allows for the quick analysis of data. OLAP cubes are also known for their ability to “slice and dice” or manipulate and analyze data from multiple perspectives. Typically the cubes are used in conjunction with a data warehouse to perform the analysis and drill downs into the data stored in the DW.
Data Mining: Analysis of large quantities of data to look for:
- Patterns (Cluster Analysis)
- Unusual records (Anomaly Detection)
- Dependencies (Association Rule Mining)
For example, if you’re a member of a frequent buyer program for a supermarket, they use the information that they collect from you and other members to look for trends in buying patterns. A trend might be that on Wednesday nights, from 6-9 PM, they sell the most Pepsi. To reinforce this behavior (and make things easier for their loyal, Pepsi-loving customers), the supermarket will make sure to have plenty of Pepsi stocked at their endcaps during this time. Or they might find that customers that purchase bell peppers also purchase ranch dressing, in which case they would put wingstack (promotional display) of ranch dressing in front of the bell papers in the vegetable aisle.
This is the second article in a two-part series. The first part outlines some of the common terms used in business intelligence (BI).
This second part is focused on helping you better understand if you should be considering the use of BI and what the possible benefits to your organization are.
I recently came across an article reporting that more than 40% of shippers will put logistics services out to bid over next year and it made me wonder just how many logistics providers are properly leveraging business intelligence (BI) tools to stay ahead of their competition?
Based on my sample of approximately 40 logistics companies, it seems that less than 20% are leveraging business intelligence to gain a competitive advantage. The good news for those 20% of companies is that with the improved visibility and analysis that BI offers them, they have a huge competitive advantage over their competition.
On the other hand, the good news for the other 80% that aren’t using BI tools is that they’re not that far behind the majority of their competitors. But in an industry where margins are increasingly thinner and competition is increasingly more fierce, is the “status quo” an adequate game plan for long-term survival?
When you’re bidding against 5 other competitors for the same business, do you know what your cost for the service that you’re providing is or are you simply bidding based on historical pricing? If you don’t know the exact cost for the service that you’re providing, then how do you know what your lowest bid can be? And if you have figured out your cost for each bid, then are you also accounting for G&A (general and administrative) costs like IT, accounting, etc? You should, since all expenses affect profitability. Also, gas prices are bouncing around like jumping beans currently. Is that figured into the cost of your services when you’re bidding? If so, how up to date is that information? A few days old is a lifetime in current market conditions.
If you don’t know the answers to the questions above, then there’s a good chance that your competitors are leveraging technology as a competitive edge over your business. The evolution of technology into the business environment is growing at an exponential pace, and natural selection is all too happy to mow over, chew up and spit out those that are slowest to adapt. Will your business be the harvester or the fodder in 5 years and what tools/game plan have you put in place to insure that happens?
There’s no room for doubting the quality of the information that you’re running your logistics business on. If that’s the case, then it behooves you to get in touch with an expert or two to have a conversation about your business and how your company can benefit by the use of some better business intelligence.
More on BI:
- Helpful BI Tools for Dynamics 365 Data Analysis
- Why BI360 May Be The Best Budgeting And Planning Software
- Overview of Power Platform