Event Review

The 3rd Service Industry Day held in Cambridge on 18 September 2012 brought together speakers from the Cabinet Office, Google, Vestas, BAE Systems Maritime Solutions, Caterpillar, Cambridge Service Alliance and IBM Software Group in thought-provoking presentations on the role of big data in service industries.

The Cabinet Office presentation discussed the challenges facing the public sector and the need for greater innovation and reform, outlining the role that data can play in enabling public service innovation, illustrated with case studies of new forms of services.

Google discussed the value of big data in their “fail fast, succeed first” approach to launching new business ideas and experimenting with new features.  A key take-away message was to “morph ideas rather than kill them”, citing the example of Google Shopping’s phases of iterative experimentation from “Froogle” to what it is now.

Vestas, the Danish energy company that owns and manages 20% of the world’s installed wind power capacity, collect large amounts of data on wind energy production for business development and operations, providing it with unparalleled fast access to data on over 20,000 wind turbines globally.  Complex climate models are shifting the value center of their business, as summarised in Christensen’s key point: “The money is no longer in the steel, it is in the data”.  Big data is used to increase certainty in decision-making and investments.

The Cambridge Service Alliance as well as Caterpillar Inc and BAE Systems all presented an exploitation case for business models and performance metrics.  Professor Andy Neely presented the latest developments in the Cambridge Service Alliance; specifically how to assess your capabilities for business model innovation and how to design measurement systems for complex services. Craig Olmstead, from CAT Global Mining, presented the challenges of building a service business within Caterpillar, and highlighted the use of the Alliance’s Capability Audit to identify strategic priorities as well as outlining Caterpillar’s approach to service and solutions. Selecting Key Performance Indicators for Complex Services was the focus for Sarah Bailey from BAE Systems Maritime Services.  She gave details of the challenges of measuring complex services and how BAE Systems and their partners identify key performance indicators.

The last speaker presented Watson – the new cognitive computer system developed by IBM that has recently won the US quiz show Jeopardy.  The presentation identified how IBM has used healthcare as a setting to illustrate what Watson can do.

In the afternoon, four parallel breakout sessions (summary below) were held to allow more in-depth discussions of the opportunities and challenges to business model innovation with big data.  Through the discussions, big data clearly appeared as a competitive advantage for organisations and service firms.  Retailer and logistics service providers were cited as examples of companies that make more money from the information in their supply chain than from product sales themselves.

However, a challenge with big data lies in how to value information and make analysis cost-effective, since almost all of the data is useless, i.e. “finding the needle in the haystack”.  In terms of capturing value from big data, firms need to balance control and ownership with the value of releasing it.  Google was cited as an example of a firm that let go of controls and shares large datasets with other companies.  Many organisations still seem reluctant to share their data even when approached with a request to “help us help you”.  Participants agreed that an evolutionary building of trust and confidence is needed for organisations to share data.  Finally, data-driven decision-making (DDD) was discussed as an important tool for organisations, particularly if used in complement with other tools such as roadmapping and scenario analysis.

The conclusion of  the Industry Day is that big data is playing an increasing role as value and profit sources in service business models.  Strategic and financial decision-making rely on big data to improve services offered to customers, but presents obvious challenges to organisations that use it.

Summary of breakout sessions

The 85 delegates broke into four groups to discuss the implications of Big Data for their organisations and industry. Each group was facilitated by a senior representative of the Alliance members, and several common themes emerged.

Opportunities for big data

The major opportunities arise from:

• Integrating data, not just collecting more of it
• Using data to predict the future, not just to analyse the past in greater detail.
• Understanding customers, and the customer’s customers, better.
• Understanding your own business, so you are better able to deliver value to customers more profitably.

There is still no agreed definition of what big data is. Some groups concentrated on the impact of the increased quantity of data available e.g. from sensors on equipment controlled or owned by the using organisation. Other groups emphasised the importance of using data from beyond the organisation, from suppliers and customers, but also data publicly available.

Business Model Innovation enabled by Big Data

There is no magic bullet for successful business model innovation enabled by big data or otherwise. Instead the groups concentrated on the challenges that must be overcome.

Culture, organisation and skills

The culture of many organisations limits the use of data arising from outside the organisation. Many companies are reluctant to share their data with suppliers or customers, often due to lack of trust. The same organisations are also wary of using data arising from these external sources, doubting its accuracy and timeliness. This is at odds with the low value many organisations place on their own data.

Making the information available to key decision makers to enable them to ask the right questions will require changes in organisations and organisational strategy. Data is often viewed as the realm of engineering or technical professionals, not senior management. New roles are required, both to manage the new information, and to promote and increase awareness across the organisation.

Making the business case

The organisations represented can see the business potential of big data, but cannot yet value the data or build a rigorous business case upon it.Effective use of big data can give a competitive advantage, yet much of the data is readily available and the success of big data relies on sharing with customers and suppliers, who often work with direct competitors.While many suppliers are offering big data solutions, there are as of yet no common standards or platforms (or even definitions) to manage big data. Significant investment is required, in data collection, people and systems, to take advantage of the opportunities.

Owning and using data

Organisations do not need to own the data they use. The costs of managing high quality data are significant, and much valuable data is readily available from external sources. However, in many cases the data gives significant competitive advantage. Discriminating between the value of the data, and the value of your analysis and use of the data, is key to exploiting big data effectively.

Regulation and privacy

Personal and commercial privacy concerns were identified as a key barrier to using big data. Many firms are reluctant to share data even with direct suppliers, despite opportunities to reduce overall supply chain costs. One group suggested a mandate could be added to government contracts, requiring them to make data available to their suppliers.

The Future

While organisations generally recognised the potential of big data to revolutionise business, the pathways to seizing this potential remain unclear. However, it was clear that organisations’ strategy must adapt in response to the availability of big data. Even those who do not exploit it themselves will face customers and competitors who do.