Climbing the Big Data Ladder Leveraging your ERP to unlock your information assets

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1 Climbing the Big Data Ladder Leveraging your ERP to unlock your information assets Melbourne, April 2012

2 Robert Hillard Robert Hillard is the Deloitte partner leading the Australian Technology Consulting practice. He is a specialist in Enterprise Information Management, which is a key part of the firm s Technology capability, and is the author of Information-Driven Business (Wiley 2010). Robert was an original founder of MIKE2.0 which provides a standard approach for Information and Data Management projects. He continues to support the initiative as the vice-president and a board member of the MIKE2.0 Governance Association, the Swiss non-profit governance body for MIKE2.0. Robert has held international consulting leadership roles and provided advice to government and private sector clients around the world. He has more than twenty years experience in the discipline of Information Management, focusing on standardised approaches including being one of the first to use XBRL in government regulation and the promotion of information as a business asset rather than a technology problem. Over many years, Robert has advised large complex organisations on their Information Management strategies and specifically how to leverage these strategies to achieve their business objectives including major transformations. 2 Climbing the Big Data Ladder 2012 Deloitte Touche Tohmatsu

3 People (will) have more time for leisure activities in the year The average work day is about four hours James R. Berry (1968), 40 Years in the Future, Mechanix Illustrated 3 Climbing the Big Data Ladder 2012 Deloitte Touche Tohmatsu

4 Despite the continuing reduction in the cost of computing, it is orders of magnitude more expensive today to introduce new products or services than it was 15 or 20 years ago. 4 Climbing the Big Data Ladder 2012 Deloitte Touche Tohmatsu 4

5 Information is produced by all processes and it is the values of characteristics in the processes output that are information R. M. Losee (November 1998), A Discipline Independent Definition of Information, Journal of the American Society of Information Science 5 Climbing the Big Data Ladder 2012 Deloitte Touche Tohmatsu

6 [In the 1920s,] experts predicted that by 1980, every single woman in North America would have to work as a telephone operator if growth in telephone usage continued at the current rate* Business Data Communications and Networking Jerry FitzGerald, Alan Dennis *At the time, all telephone operators were women 6 Climbing the Big Data Ladder 2012 Deloitte Touche Tohmatsu

7 Information Growth doesn t just go on for ever 1990: price of storage hit the important physiological threshold of US$1 per megabyte Apparently insatiable growth in business data but we expect growth will slow and transition to the new economy in the future 2030s? Climbing the Big Data Ladder 2012 Deloitte Touche Tohmatsu

8 What is big data? Big data can be very small (e.g., avionics) Large datasets aren t necessarily big (e.g., transactions) Big data is complex and hard to isolate (e.g., toll roads) Big refers to big complexity rather than big volume. Of course, valuable and complex datasets of this sort tend to grow rapidly and so big data quickly becomes truly massive. 8 Climbing the Big Data Ladder 2012 Deloitte Touche Tohmatsu

9 Traditionally information is governed as a system Value is imposed Information Trading Platform Increasingly trying to put the right motivations in place Moving to an information economy Value is built into the price 9 Climbing the Big Data Ladder 2012 Deloitte Touche Tohmatsu

10 ERPs are the trading platform not a bucket The investment in enterprise applications has provided a foundation for master data Master data is a set of keys not a map of what s behind every door Sensors, SCADA, mobile devices, location aware services et cetera are all creating masses of data that should not necessarily go into the ERP Finance, though, can argue a position as the information Tsar 10 Climbing the Big Data Ladder 2012 Deloitte Touche Tohmatsu

11 Value needs to be modelled not calculated Big data adds complexity to the organised, justifying consolidation at the rate f=log c/i (l+1) where f=complexity factor, c=cost per system, i=cost per interface and l=number of legacy systems Data should be valued without trying to identify all of its uses (6 standard methods) ERP master data should be used to provide a standard language and point of agreed value it is not the single enterprise store Introduce information currency as real concept for exchanging value, ROI should include both repayment of system cost and the impact on the information economy 11 Climbing the Big Data Ladder 2012 Deloitte Touche Tohmatsu

12 The six methods of valuing information Intrinsic Value of Information How good and easy to use is the data versus how likely are others outside the organization to have it also? This the presumptive value of information, enabling apples-tooranges comparisons. Business Value of Information The value of information to a business process: How good is the data? How applicable to the business or a particular business process is it? How quickly can we get fresh data to the point of the business process? Performance Value of Information Value of information to business objectives, represented as key performance indicator (KPI) targets: How much does having a unit of information incrementally contribute to moving closer toward all n KPI targets over a given period? Where: i = influenced C = control Economic Value of Information The bottom-line financial value for the information asset: The Performance Value of Information (PVI) for a revenue metric, less the cost of acquiring, administering, and applying the information. Loss Value of Information The cost of not having information: What would it cost to replace the data, and what is the financial impact to the business if the data were lost over a time period (t)? Market Value of Information The income that can be generated by selling, renting or bartering with this information. How much is a business partner (p) willing to pay for access to this information? 12 Climbing the Big Data Ladder 2012 Deloitte Touche Tohmatsu 1

13 Putting a value on decommissioning A simple approach to estimating the value of decommissioning legacy systems is based on the complexity that they add to the introduction of new services. Using the past as a basis, c is the investment per new system and n is the number of system builds expected over a given period. Investment cost for a domain is therefore c times n. However legacy systems add complexity at a rate that rapidly increases initially before trailing off (logarithmic). The complexity factor (f) is dependent on the ratio of the cost of software to development (c) to the cost of interfacing (i): f=log c/i (l+1) The complexity factor can then be applied to the original investment: c x n x (f + 1) Note, efficiencies in interfacing similarly provide benefit. As the cost of interfacing drops the logarithm base increases and the complexity factor naturally decreases. f c = likely cost per system n = number of likely system builds in 5 years i = cost per interface l = number of legacy systems in domain f = complexity factor This is only a method of identifying a savings trend, but it provides a good starting point for more detailed modelling of benefits. l 13 Climbing the Big Data Ladder 2012 Deloitte Touche Tohmatsu

14 Climbing the Big Data Ladder 2012 Deloitte Touche Tohmatsu

15 General information only This presentation contains general information only, and none of Deloitte Touche Tohmatsu Limited, its member firms, or their related entities (collectively the Deloitte Network ) is, by means of this presentation, rendering professional advice or services. Before making any decision or taking any action that may affect your finances or your business, you should consult a qualified professional adviser. No entity in the Deloitte Network shall be responsible for any loss whatsoever sustained by any person who relies on this presentation. About Deloitte Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee, and its network of member firms, each of which is a legally separate and independent entity. Please see for a detailed description of the legal structure of Deloitte Touche Tohmatsu Limited and its member firms. Deloitte provides audit, tax, consulting, and financial advisory services to public and private clients spanning multiple industries. With a globally connected network of member firms in more than 150 countries, Deloitte brings world-class capabilities and deep local expertise to help clients succeed wherever they operate. Deloitte's approximately 170,000 professionals are committed to becoming the standard of excellence. About Deloitte Australia In Australia, the member firm is the Australian partnership of Deloitte Touche Tohmatsu. As one of Australia s leading professional services firms. Deloitte Touche Tohmatsu and its affiliates provide audit, tax, consulting, and financial advisory services through approximately 5,400 people across the country. Focused on the creation of value and growth, and known as an employer of choice for innovative human resources programs, we are dedicated to helping our clients and our people excel. For more information, please visit our web site at Liability limited by a scheme approved under Professional Standards Legislation. Member of Deloitte Touche Tohmatsu Limited 2012 Deloitte Touche Tohmatsu

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