It may seem like a boast, but the facts back it up: Every single industry can benefit from modern analytics.

While some companies have moved quickly to leverage advanced customer insights and operating information, modern technology provides analytic opportunities for every business.

But some decision makers may still drag their heels if the conversation regarding analytics remains theoretical. Concrete examples of applying analytics may help motivate managers to seek out the advantages analytics can provide.

Saving money – without a big capital investment

The fastest way to see a return on any investment when implementing a new business practice is to realize a measurable increase in revenue or decrease in spending. A recent Deloitte study shared the example of a company that saved $1.5 billion in expenditures by utilizing analytics, simply by "being smarter" without investing more capital. The company practiced regular data mining and analysis of its product supply network to reduce costs associated with inventory management, transportation and warehouse procedures.

Discovering the quickest path

It's all well and good to talk about how leveraging internal and external information can reduce waste and improve efficiency. But consider instead the impact of analytics on medical emergency responders, where wasting time is a matter of life and death. Forbes detailed how Toyota launched a new service for Japanese ambulance drivers and medical helicopter pilots to assist with just that. The automaker created an algorithm to analyze data regarding vehicle crash specifics so responders can determine the best possible route for pick-up and hospital delivery. The information collected and analyzed by the system should ensure crash victims receive the care they need as quickly as possible. Watching an ambulance speed through the city can be more convincing than any spreadsheet projection.

How to get started

When beginning with analytics, a company should start by ensuring the data coming from its operations and transactions is organized in a way that supports easy query, "slicing and dicing," and makes key performance indicators visible. After two decades of implementing databases and business intelligence systems, many firms have reached the stage where they can gain actionable insights from their data.

It then makes sense to invest in software tools for analytics – but companies should first consider the people they have who will use that software, and the skills they currently possess.

Few business analysts have the skill set of a true data scientist – the "unicorn" expert with deep knowledge of math and statistics, programming, databases and real business domain knowledge. In fact, it's still uncommon for a mid-sized company to have on staff an individual whose sole responsibility is "data science." But that need not stop a business from getting results from analytics. There are easy-to-use software tools designed for the business analyst that automate many of the steps in applying analytic methods.

One of the best maxims to follow when getting started is the classic "do something small, simple, now." Don't try to build a total analytics solution initially. Simplystats, an analytical advice blog, suggested organizations begin application of analytics with specific goals in mind.

A best practice for any process or software implementation is to start with a small project - maybe even a single performance indicator. For example, a company with products or services where demand from different market segments varies with price can gain a great deal from a project using revenue optimization to adjust prices dynamically, as opposed to relying on static prices. Disney did this starting with just one Broadway show, which became a huge success.

Analytics when the stakes are high

Modern business leaders are making fewer "seat of the pants" decisions without data – that practice isn't defensible in a world of abundant information and powerful software. Even when data is incomplete and there's plenty of real-world uncertainty, analytics can help by quantifying that uncertainty, and assessing by how much results can be worse – or better – than expected.

CFO magazine said the results of analytics models belong in the boardroom. Whenever a company head wants to make a bold new decision, his or her plan should be backed by analysis and modeling of future scenarios, and should include processes to stay on top of progress and make adjustments, or even cut losses if the numbers don't match up to success metrics.

The modern information age generates more data than ever, but data doesn't automatically yield insights. That creates a challenge for business leaders to gain insights from data, and use those insights to make smarter decisions. Effective use of data-driven analytic models, plus modern data visualization, can yield that insight – and help your company stay ahead.