Big Data may be proliferating at an astonishing pace, but managing it isn't cheap. Business analytics can eat up a huge portion of a company's budget, and it's all the easier to let costs get out of control when they're spread across different departments and functions.
But the cost of implementing business analytics shouldn't dissuade you from trying to make the most of the data at your disposal. That's because business analytics can be a powerful tool for cost reduction across the organization. While it may be expensive to implement the strategies and software tools to successfully manage your data, business analytics can be a powerful tool for cost reduction across the business. Let's take a look at some of the ways you can use business analytics to lower your operating costs all around.
Moving inventory is the lifeblood of many companies — if you're not in manufacturing, you're probably in shipping and logistics, distribution, and retail. Even if you don't have many supplies in your office, you and your employees will still need a certain number of pens and pads to get the job done — but too many is just a waste of money.
Tracking and managing inventory is one way that business analytics applications can help with cost reduction. With smart inventory tracking, it's easy to identify purchasing patterns, so you can always have just the right amount of inventory available — and that will free up extra cash.
Most organizations start to implement a Big Data strategy without even realizing that they have different types of data in their possession. There's light data, which is the data that organizations collect and use to make decisions — things like survey results, security reports, current employee data, and any other data leverage in the making of business decisions is light data.
Then there's dark data — the data that businesses collect and don't use. Some of this data might appear alongside light data in things like survey results, or it might occur in emails and recorded customer calls, logs, former employee data, geolocation data, and so forth. Any data that the company collects but doesn't use is dark data — if you think of Big Data as being like an iceberg, dark data is the portion of the ice that lurks beneath the surface.
You need to make use of this data. Some of it may be critical enough to change the outcome of your data analysis. Some of it could leave you vulnerable to hackers. You never know what's in your organization's dark data, how valuable it is, or how hackers might be able to manipulate it to get into your system — not until you start exploring those depths through business analytics.
Employee churn is a huge expense for most companies, with the average cost of voluntary turnover currently at about $15,000 for each employee that leaves. Advanced business analytics can help you reduce those expenses by helping you better choose candidates that align with your company's values and core culture. In addition to analyzing the data you collect about employees pre-hire, advanced analytics can help you collect employee satisfaction data through surveys and other anonymous collection tools, and then analyze that data to make changes that will help address causes of employee dissatisfaction. Employees will feel more engaged and happier in their positions.
The power bill might not be the first thing you think of when it comes to cutting costs with data, but your company's use of energy resources is one of the easiest things to track and adjust when implementing data analytics for cost reduction. How much are you spending to keep the lights on when no one is in the office? Are you paying for heat or A/C, only to have employees complain that it's too hot or too cold? With smart energy management, you can set the lights to turn off automatically, for example, or take more control over the temperature in your offices. The savings could be significant.
Are you looking for a way to boost your productivity and profits while cutting costs? It's the best of both worlds — and a business analytics strategy can give it to you. Don't wait any longer — it's time to hop on the Big Data bandwagon.
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