To do this, you can use a wide variety of analysis methods including A/B testing, logistic regression and association rule learning. You can do this mostly manually or employ advanced technology to help with this. Companies today often use algorithms, machine learning and more. Standard query language, or SQL, is the standard for communicating with a database today, but that may change in the future.
How you present your data and insights is also important. You want to display it in a way that people can easily understand and that will inspire them to take action. Visualization is particularly effective at this.
You can purchase software and other resources and complete your big data analysis, or you can hire another company to do this work for you. These kinds of companies offer what is sometimes called Big Data as a Service or BDaaS. This provides you with the power of that company’s resources and expertise without having to make a big initial investment or spend too much time on the subject.
Why Big Data Analytics Is Important
They say knowledge is power, and big data analytics is a perfect example of this. Data and the insights you can gain from it provide you with a deeper understanding of your business, your customers, your employees and more. The potential for this endeavor is far-reaching. It could produce results related to almost anything you can imagine, given the right resources.
These data insights enable you to predict the future and learn from mistakes made in the past that you otherwise might not have even known about. Every day, businesses spend money on things they don’t really need or overpay for certain commodities. With the power of big data, you can change all of that.
General Electric produces a lot of data. Most of their machines, which operate in power plants, hospitals, factories and many other places, produce huge amounts of it. GE collects this data, analyzes it and then uses it to make its machinery operate more efficiently. The company estimates that data could increase the United States’ productivity by 1.5 percent and increase the average national income by 30 percent over 20 years through cost savings.
Another big data success story comes from UPS, which, as the company says, specializes in logistics. The company makes nearly 17 million deliveries every day, so it has a lot of data to work with. It began tracking the performance of its vehicles in relation to routes, idle time and maintenance and then analyzes the data using algorithms. The result was 39 million fewer gallons of fuel burned and 364 million driving miles avoided.
Big Data’s Human Element
Big data analytics might bring to mind imagery machines humming and crunching numbers, and while that’s certainly part of the equation, there’s a human element too. Someone needs to be there to organize the data collection, determine what patterns to look for and, vitally, take action based on the resulting conclusions.
Some companies might outsource this work to a company that specializes in it, while others might prefer to hire an internal worker to do it or to learn how to do it themselves. Either way, the process requires a human to manage it. And the employees at your company need to implement the changes that your data work suggests.
If you plan on analyzing your own big data internally, look for someone with experience in computer programming or computer science, mathematics and statistics. It’s also helpful for this person to understand business and accounting for businesses. Big data analytics is a young field, however, so these requirements might change in the future.
If you want to boost your resume in the field of big data, you can pursue any number of certifications in the field. These programs will hopefully teach you something and help you get a job. Technology companies such as IBM, SAS, MongoDB offer a variety of certifications. Some of the tops ones include CCP Data Scientist, MongoDB Certified Developer, Oracle Business Intelligence and SAS Certified Data Scientist.
The Future of Big Data
As mentioned earlier, big data is still a young field. It’s expected to grow incredibly quickly in the coming years and will likely change a lot. Getting started now, though, can help companies avoid having to play catch-up in the future.
As the field progresses, the volume of data will continue to increase. Wider varieties of data types will be generated and collected more quickly, and more organizations will have access to data. In the future, the vast majority of businesses will likely rely on data to run their businesses and drive growth.
Tools for analyzing data will also improve. They’ll become more automated and easier to use so that they’ll require less technological expertise. The business model of big data as service will likely continue to grow, as will use of the cloud and machine learning. We might have access to more real-time data insights as well.
Although the field and the related technology are still developing, it’s already impacting almost every industry. Getting involved now would be a worthwhile investment, especially since it can save you money through reducing indirect costs and optimizing other areas of business operation.
In the not-so-distant future, all aspects of a business will use data to improve their operations. Accounting will use it to track and analyze spending and income. Supply chain managers will be able to harness actionable insights from data to optimize procurement systems. Management will be able to increase profits both by improving performance and cutting costs, all thanks to insights gleaned from big data.
The Value of Indirect Spend Procurement Consulting
Even if you don’t use big data to identify cost savings, looking into your indirect expenses is still a smart and potentially lucrative endeavor for any business, especially since it typically comprises between 15 and 27 percent of total revenues. You might be surprised at the extent of the cost savings that you come across when you analyze your indirect expenses.
At Dryden Consulting, we’re experts at combing through companies’ spending patterns and identifying ways to make that spending more efficient and cut costs. Because of the wide range of spending that companies typically manage, this can be a complicated process, but we have the tools and skills to produce results.
We’ve worked with companies like Coca-Cola, Microsoft and Nestle to analyze and optimize their spending to improve their bottom line. We can do the same for you. If you want to find the hidden savings that exist in your daily operations, we can help you collect data on and analyze your indirect spending. We offer a variety of solutions that can help you save money and increase profits. If you want the experts on your side, contact us for indirect spend procurement consulting.