One of the key insights from the 2018 Gartner CIO Agenda Report is that the digitization of businesses is transforming the role of the CIO from “delivery executive to business executive – from controlling costs and re-engineering processes to driving revenue and exploiting data.” Most of us are familiar with the phrase “data is the new oil” and CIOs are more than aware of the rapidly increasing volumes of information flowing within and between businesses.
Using this data to create value for the business and secure a degree of competitive advantage, however, is another matter. Collecting massive amounts of data and pooling it with information assets from other companies is not always delivering the benefits promised by vendors of big data solutions. Despite these challenges there are companies forging paths through the data monetization jungle.
Airbus flying high on data
From a big data perspective, Airbus has adopted a data pooling approach with its Skywise platform linking suppliers and customers. Earlier this year, Tom Enders, the CEO of Airbus stated that data was “central” to the future of his industry and the company’s partnership with Palantir Technologies to build Skywise is a demonstration of this belief. By making sensor-collected performance data from aircraft along with other sources such as constantly monitored weather data available to component suppliers, all parties can develop a better understanding of where systems are not working as planned.
An Airbus A350 contains around 6,000 sensors and generates over 2.5 terabytes of data each day it is in operation. The collection, analysis and sharing of this data allows suppliers to improve manufacturing and development processes and contribute to predictive maintenance scheduling for customers such as EasyJet and Delta. The system is still being rolled out, but it is anticipated that operational interruptions affecting flight departures could be reduced by 15% while fuel usage could be significantly reduced through real-time adjustments to flight plans based on environmental and operational conditions.
How analytics can improve health and the bottom line
Another large-scale, data processor that is building a highly defensible business in the health informatics sector is IBM with its Watson AI platform. In 2016 the company spent $2.6 billion buying Truven Health Analytics and, in the process, acquired data on the cost and treatment of over 200 million patients. While IBM Watson Health is already benefiting patients through faster diagnosis of conditions it is also creating a virtuous circle for IBM as more hospitals join in and contribute to its platform and the AI embedded in the system learns through the results of its diagnoses.
On a smaller scale many companies are adopting innovative approaches to analytics to better understand consumer behavior and raise profits. Point Defiance Zoo in Washington State had long realized that weather conditions had a massive impact on visitor numbers. On a sunny day up to 6,000 people might visit the zoo but rain the following day could reduce this to 1,000. As a large proportion of the zoo’s costs were fixed in the form of staff wages these attendance peaks and troughs were significantly impacting the bottom line. Using IBM’s Cognos 10 business intelligence system to analyze ticket sales, historical attendance data and a real-time weather feed the company was able to predict staffing requirements for any given day over the following week.
Protect your data assets
Despite the potential upside there are dangers for companies outsourcing their data analytics function to third parties. In many cases, such as the Airbus example, there are benefits to pooling data and using the expertise of companies operating data processing platforms. Where strict rules are enforced as to who owns the data once it has been processed, who else can see the results and what happens to it once the processing has taken place many problems can be avoided.
As consultants McKinsey recently demonstrated, however, data is reshaping value chains across a number of industries. Many functions of the firm can be outsourced to those with core expertise in delivering on those activities. The danger for companies, according to McKinsey, is that data may be their most valuable asset and entrusting it to others could be a costly mistake. In industrial settings this might take place where the data generated by your plant machinery is collected and owned by the equipment manufacturer.
It is also important to avoid being locked in to a single platform where switching to a new provider can be difficult and costly. The recent announcement that the EU is investigating Amazon for the way it uses data from third parties selling on its platform is a case in point. The claim is that Amazon may be using its overview of all sales data to potentially create and sell its own products to compete with its own customers.
Enriching the customer experience with data
Business value chains are being transformed through the massive collection and processing of data across a range of business processes. At the same time consumer expectations are rising with expectations of low prices, fast delivery and massive choice combined with personalized service. Recent research from CRM vendor Salesforce of 6,700 consumers and business buyers illustrates the challenges faced by companies as they try to navigate this new landscape.
According to Salesforce, 72% of consumers and 89% of business buyers say they “expect companies to understand their unique needs and expectations.” Achieving this requires access to consumer behavior and sales data across a range of sources. Digital giants such as Amazon and Netflix are able to pull together many of the pieces of this puzzle from their vast troves of user data, but smaller companies struggle to achieve the same partly through lack of access to the right sources but also lack of experience in managing data for competitive advantage.
Solutions that can pull together disparate and siloed information to provide a richer customer experience will be a solution to some companies. As IDC’s Maureen Fleming recently stated, “Companies who are truly digitally capable will be able to connect these disparate data sources, pull critical business-level data from these connections, and make informed business decisions in a way that delivers competitive advantage.” For many companies this is still a difficult journey but the rapid deployment of AI and machine learning to analytics and data processing makes it a vital journey if they are to survive the new wave of competition that is coming.