“The CIO needs to ensure that they champion a value-based and consumption-focused approach to their enterprise data strategy,” say Dr David Salmon and Dr Tadhg Nagle from UCC.
Dr Sammon and Dr Nagle are programme directors of the MSc Data Business, Irish Management Institute course at University College Cork (UCC).
Dr Sammon is a lecturer in the Department of Accounting, Finance and Information Systems at UCC. His current research interests focus on the areas of conceptual data modelling, data/information management, theory and theory-building, and redesigning organisational routines through mindfulness. David has published extensively in international journals and conferences. He is an associate editor of the Journal of Decision Systems and co-author of the book, Enterprise Resource Planning Era: Lessons Learned and Issues for the Future (2004).
Dr Nagle is a lecturer in the Department of Accountancy, Finance and Information Systems at UCC. With a background in management information systems, Tadhg has worked as a senior software engineer in the Western Union division of Fexco. From there he took up a position within the Digital Enterprise Research Institute (DERI) as a Business Analyst Lab Leader in examining the impact of emerging technologies on the Irish e-learning industry. Currently, Tadhg is involved in a number of industry groups such as IT@Cork and Open Data Ireland, which is highlighting the potential for open data nationally. He is also part of FuturICT, which is a €500 million bid to build a pan-European information system simulation platform.
What should be the main features of a company’s data business strategy?
One of the key features of a data business strategy should be the ability to map the flow of data through the organisation with the view to identifying current data deficiencies or future data opportunities for the business model. In essence, a data business strategy should promote simplicity and should be designed around a mindset of ‘our data is working for us’ and not ‘we are working for our data’.
What are some of the main responsibilities of a CIO’s role, and how much of their time should be spent on business issues?
The CIO needs to ensure that they champion a value-based and consumption-focused approach to their enterprise data strategy. The key responsibility of a CIO is to ensure that an organisation’s data capability is a springboard and not a millstone to business success. A springboard encompasses having good quality data that seamlessly supports solid decision making and business operations. A millstone is where the lack of trustworthy data creates huge amounts of ineffective work to make basic business decisions. The CIO needs to spend at least 80pc of their time on business and data-related issues. In an effort to do this the CIO must establish if the enterprise data model supports the business logic of the ever-changing business model.
What are the big trends and challenges in data business, and how can the CIO plan to address them?
The increased proliferation of data requirements, data sources, and data technologies are key trends and challenges. While an increasing choice of data sources and technologies provide more opportunities and capabilities, they bring a lot of overhead with regards to ensuring successful management and implementation. The CIO will need to focus on business data consumers and their requirements and will need to challenge the often dominant and unhealthy focus on the best piece of technology for the job! Therefore, the realisation that technology is not the solution to data problems needs to be communicated by the CIO throughout the business as frequently as possible.
What metrics or measurement tools would you recommend to CIOs to measure how well their data is performing for their business?
The CIO needs to present a challenge to the business on their data practices and they need to champion more mindful behaviours around their business data to avoid bad data. In this case, we define mindful as attention to detail and continual awareness. In an effort to do this the CIO must frequently challenge business users to establish how valued the enterprise data model and enterprise data quality are, and if they are calculating the cost of bad data. A simple approach to presenting this challenge is through the use of the Information Supply Chain (ISC) canvas. The ISC canvas enables organisations to map the flow of data through the organisation. By being able to map the flow of data using the Information Supply Chain, organisations are better able to identify any current pain points, while also providing a basis from which future data improvements can be planned.
Are there any areas where data can improve, and what are they?
If the CIO frequently asks business users a “how many” question (e.g. how many customers do we have?) and the question cannot be answered within a reasonable timeframe and with reasonable accuracy, then the CIO needs to establish why. In fact, in recent trade press coverage, the CIO of the future is defined as the Chief Integration Officer and there is no doubt that the integration of data/information is an area where all organisations can improve. In fact, data silos/islands of information are the most common and most onerous aspects defining organisations and their business data at the present time. One of the most paralysing effects of data silos/islands of information is that they increase the difficulty in answering the simplest of questions. However, to achieve the golden record within the organisation will require a deconstruction of these data silos/islands of information. Therefore, the CIO should highlight areas of integration that will have significant business impact and value as a first step toward data silo extinction.
From your experience, can you give examples of some interesting data business projects that companies have lined up and how they have contributed to the business?
Over the past 12 months we have seen quite a large number of data business projects in the areas of sales, procurement, manufacturing and customer service across various organisations. The focus of these projects has tended to centre on the design and development activities associated with analytics models, data models, visualisations and dashboards, and maturity frameworks. Particular examples include illustrating how data visualisations can: improve procurement decisions, improve the effectiveness of customer service, and change the behaviours of sales teams. Further examples also include the development of analytics models to better understand: mid-market segmentation, customer churn, manufacturing efficiency, and sales order credit holds.
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