Big Data – The Promise of ROI
The question of ROI from big data hotly contends with strong points on each side of the divide. However, several businesses have proven used cases that indicate they have managed to reap benefits that are above and beyond the initial investment.
Other businesses using big data believe that democratization will cut the initial costs and has what many need to make the investment worthwhile.
Regardless of the number of divergent views, one thing is clear; specific industry segments have made such monumental gains with big data. This alone would appear to suggest that data science application in modern business are likely to weather the storm and may soon be very profitable and widely used.
Business Outcomes based on Investment in Big Data
Research undertaken by major surveys by companies such as GM, IBM and Accenture draw very strong conclusions in support of big data.
In Companies using big data, 92% of executives are satisfied with the results with a further 89% of these executives rating big data as very important. It is very impressive given show computing costs has reduced; 33% reduction in computing cost, 38% reduction in storage costs and 27% reduction in bandwidth costs.
Walgreens and Kroger
Walgreens and Kroger can be categorized as the retail business involved in the provision of quality health services; through in-store health clinics.
In these stores, big data is an essential part of decision making used by clinicians at the point of care. Using the big data, the clinicians have been able to provide better patient assessment, provide good and reliable recommendations that improve overall health and reduce or avoid future medical costs.
In practice big data allows the clinicians to take note of common errors like an unfilled prescription. This keeps their patients healthier and on track with treatments.
Their data source includes 7.5 billion events covering 100 million people and includes information such as demographics, diagnoses, enrollment, procedures and data from managed care plans.
The organization leverages its big data successfully in a joint venture with Dunhumby. For Kroger big data has seen significant improvements in patient health and customer loyalty. Today over 90% of their business are directly from the loyalty card holders. The novel scheme saw the loyalty program grow to 60% redemption rates and an increased revenue stream in the region of $12 billion. The loyalty program saw this business remain profitable even through the recession.
Southwest and Delta Airlines
As companies offering a service, customer relationship management is essential. The main tools in use in both these fast growing airlines include social channels and other interactions.
Southwest uses speech analytics to improve its interaction with customers and personnel. Southwest also uses big data to gain insights on customer online behavior and actions. This data analysis has improved interactions with customers and led to increased loyalty over one year.
Delta has used big data to help with one of air traveler’s worst nightmare – lost luggage. With over 130 million bags tracked each year Delta introduced tracking options for customers from mobile devices. The increased peace of mind and has been downloaded 11 million times. The move has branded Delta a very customer-centric airline and has seen the company enjoy plenty of return business.
UPS – Logistics
This busy package delivery organization ships over 4 billion items annually using almost 100,000 vehicles.
It goes without saying managing to operate smoothly is hectic, and big data is used for fleet management. The company has on-truck systems that assist with routes, idle time, engine and predictive maintenance.
Since the inception of the big data program UPS has; saved 39 million gallons of fuel and avoided unnecessary driving 364 million miles just using the analytics software. The next level appears to be using the program to improve the operational efficiency of their airplanes.
Telekom – Sprint and Anonymous
Sprint is busy and big telecom service provider. Sprint handles 10’s of billions of transaction daily for approximately 53 million users. Their big data analytic system and real-time intelligence in network operation have seen the company enjoy 90% increase in network capacity.
From the onset, Sprint focused big data initiative son improving customer experience and customer turnover owing to network error rates.
Government – The City of Chicago and IRS
The IRS uses big data to curb identity theft fraud and to track tax-related payments. The system is useful ensure compliance with tax rules and regulations. The system has been a great success, and the IRS has prevented billions in losses from fraud and identity theft and recovered in excess of $2 billion over the last 3 years.
The City of Chicago installed sensors across the city that check air quality, sound volume, light intensity, heat, precipitation, wind speed and cell phone traffic. The objective is to make the city and environs cleaner and safer and to attract technical researchers.
Gaming and Online Education – Skillsoft and Jagex
Skillsoft specializes in the provision of professional online education. The company uses big data to learn, improve and apply knowledge to 19 million users and 60,000 learning assets. They use direct email and surveys to customize learning content. The use of big data systems has seen improved customer engagement with 128% improvement in customer engagement.
Following its participation in a big data conference, Jagex started using big data to pore through 10 years of game content and 220 million gamer accounts. The objective is to provide accurate in the game recommendation to subscribers. One of their bestselling games RuneScape was a free extremely popular Multiplayer Online Role Playing Game (MMORPG). The use of data science led to improved and increased engagement, revenue, and quest completion rates.
While all the above companies and several more have successfully earned beyond their investment, there is a growing number who believe big data does not promise ROI.
Why is this?
Based on the above successful use cases, it would be safe to suggest that big data model that succeed have to bear a very clear understanding of the industry and the opportunities. This conclusion is based on the manner in which all the above companies have used data science to increase revenue generation.
Their approach generally tends more towards timely and customer or product centric decisions than toward actual product improvements. Processes it would appear are more important to success than the actual product.