We’ve all heard the term “Big Data” and its effects on how the modern organization conducts its business. The story is as follows: the typical company sits on a veritable goldmine of data within its walls that can be leveraged to improve the efficiency of the overall enterprise. By taking a deeper dive into this data and funneling it into various corporate channels, the benefits are numerous.

Does this story sound familiar? Of course it does. The basis of “Big Data” is the foundation of spend analytics, a longtime weapon in the arsenal of the modern Chief Procurement Officer. Spend analytics has long-been perhaps the most critical tool available to procurement executives and professionals, as the intelligence gleaned from spend analytics efforts can be linked to the sourcing team in times of negotiations with key suppliers. Critical spending patterns, trends and anomalies are all uncovered with a spend analytics tool, allowing the procurement / sourcing function to drive more strategic value in their supply management programs.

So, we’re now in an age where Big Data rules the business roost. Every function, from IT to HR to treasury to finance to marketing, has included some measure of data management within their programs. Today we’re focused on the emergence of Big Data into the world of travel and expense management, one of Ardent’s core research coverage areas.

Years ago, the improvement of policy compliance or a reduction in travel- and expense-related costs was often at the top of the priority scale for the vast majority of organizations. What we’ve seen over the past few years is a growing trend in the direction of analytics; more and more enterprises are realizing that through the intelligence generated from analytics, they can transform their travel and expense management programs into well-oiled machines that drive true corporate value beyond simple cost and compliance improvements.

Think about the various avenues in which the typical finance, procurement or travel management exec can tap into through analytics or data reporting:

• Calculating the exact return on travel investments. This is perhaps the most “revolutionary” concept of injecting real data into travel and expense management programs. Often times, travel is just another series of budgetary line items within the average organization. Imagine a business world in which sales and operational directors can look back at both sales opportunities and related business trips and exactly quantify the ROI of that travel investment. This intelligence can go a very, very long way in determining just how effective business travel is in improving business development.
• Understanding the travel supplier base. Out of all the analytics / data-related items discussed here today, this item has the most alignment with the typical procurement executive. Spend analytics has often been utilized to consolidate and better-manage the vast array of suppliers within the average organization; this concept is no different in the travel management world. Travel spending can get mightily out of hand if too many non-preferred suppliers are in the mix, thus, data and intelligence into this supplier base can effectively help reduce costs and improve policy compliance.
• Pinpointing, then forecasting, instances of non-compliance. Compliance is still an issue for any organization that leverages business travel to improve their organization and reach clients, customers and other corporate locations. Back-end data can easily help pinpoint instances of non-compliant travel and help finance execs (or whomever is tasked with managing the travel function) rectify these situations. In a similar sense, being able to forecast these instances (pre-trip) can help transform how the overall organization manages its travel budget and related costs. Forecasting, the strategic arm of Big Data, leverages “now” data to prepare the business for the future.

Our “Digging into the Data” series will continue with a foray into the world of one of my favorite topics (and one I hope you are getting more fond of) contingent workforce management and how Big Data is revolutionizing how organizations manage everyone who falls under the contingent workforce umbrella.

Tagged in: Big Data, Christopher Dwyer, Complex Categories, Data, T&E