Facet Publishing have announced the release of the second book in the iResearch series, Information Systems: Process and practice, edited by Christine Urquhart, Dr Faten Hamad, Dr Dina Tbaishat and Alison Yeoman
Design and evaluation of information systems and services have remained an area of study and research in many disciplines ranging from computing and information systems, information and library studies, to business management. Each discipline aims to address a set of unique challenges as they are seen from their disciplinary background and perspectives. This results in research that often fails to take a holistic view of information systems including technologies, people and context. This second title in the iResearch series addresses this challenge by bringing together different viewpoints and perspectives of information systems design and evaluation from the contributors’ own diverse and yet complimentary areas of teaching and research interests.
Co-editor Christine Urquhart said, “This book attempts to bridge some of the gaps between discrete areas of research that information professionals could use to design helpful and effective information systems and services. Our aim is to provide a critical analysis, with supporting case studies of library and information service and systems architecture – in a very broad interpretation of the term architecture”.
The book will be essential reading for researchers in information science, specifically in the areas of digital libraries, information architecture and information systems. It will also be useful for practitioners and students in these areas seeking to understand research issues and challenges and to discover how they have been handled in practice elsewhere.
iResearch series editor G G Chowdhury said,
‘This is not just another book on information architecture that focuses on content architecture alone; the research and development activities reported in this book also cover the other end of the spectrum concerned with service evaluation, performance management and library assessment. The 14 chapters in this book, written by academics and researchers from different research backgrounds and viewpoints, offer a significant contribution to research and practices in the architecture, design and evaluation of online information systems and services.’
About the authors
Christine Urquhart was a full-time member of staff in the Department of Information Studies, Aberystwyth University. Since retiring from full-time teaching she has continued to pursue her research interests.
Dr Faten Hamad is an Assistant Professor in the Library and Information Science Department, University of Jordan.
Dr Dina Tbaishat is an Assistant Professor at the University of Jordan, Library and Information Science Department.
Alison Yeoman was formerly a Research Officer in the Department of Information Studies, Aberystwyth University and is now an independent researcher.
With contributions from: Sally Burford, Catherine M. Burns, Karen Colbron, Adam Euerby, Fernando Loizides, Aekaterini Mavri, Paula Ormandy and Cristina Vasilica.
For more information about the book and to read a sample chapter click here
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Guest post by Andrew Cox, co-author of the forthcoming book, Exploring Research Data Management
In a globalising world the future is complicated. It is not simply a matter of new trends impacting library work in clearly defined ways. Rather change seems to be impacting our work in complex ways. In a recent report on the future of academic libraries (Pinfield, Cox and Rutter, 2017) we sought to address this complexity by proposing that we think in terms of nexuses of change. Two major ones we identified were:
- “The dataification of research” -combining trends such as open access, open science, text and data mining, artificial intelligence and machine learning, the internet of things, digital humanities and academic social networking services, and
- “Connected learning” -incorporating changing pedagogies, learning analytics, students as customers, social media, mobile computing, maker spaces and blurring of space uses.
A story that seems to be threaded through these changes is the growing importance of data.
Research data management
Thus one aspect of change in research practice is the way that the valued outputs of research are increasingly not confined to written outputs, but also seen to lie in the underlying research data. If made discoverable and useable these data can be the foundation for new research. Research Data Management is the emergent set of professional practices that supports this emphasis. Librarians have had a big part in how this story has unfolded.
Text Data Mining
Another data related change in research is the way that texts in the library are increasingly to be seen as data for Text and Data Mining (TDM). When there are literally hundreds of thousands of research papers on a topic, a manually conducted “comprehensive literature review” becomes an impossibility. Rather we will need the help of text mining algorithms that seek out patterns in the corpus of texts. It is libraries that are seeking to create the legal and technical infrastructure in which TDM can be carried out.
Learning is also undergoing a data revolution. Usage behaviour as library or learning analytics is another key area of development. If we can connect the data we have about user visits to the library, book issues and resource downloads, activities in the virtual learning environment and in the classroom, we can produce a better understanding of learner behaviour to help customise services. Librarians could be at the forefront of mining this data to improve services.
Data: structured or unstructured?
Granted, this storm of interest in “data”, may disguise different usages of the term. Research data could be qualitative data, though they are perhaps most valuable and vulnerable when derived from data intensive science. TDM is concerned with text as unstructured data. Library and Learning analytics are based primarily on structured, log file data.
The ethical issues
At the same time our sensitivity to the ethical issues around data is rising. How can users be given appropriate control over their own data? What restrictions need to be placed on commercial companies’ use of data about our online behaviour? Can libraries themselves retain users’ trust while exploiting the benefits of learning data analysis for service improvement? There are also massive challenges around data preservation in all these contexts. The professional knowledge of librarians and archivists need to be translated to meet the challenges of data curation. Data literacy, as an aspect of information literacy, will also need to be part of librarians’ training offer.
All these trends suggest that our skills in managing, interpreting and visualising, and curating data, in ethical and legally safe ways, will be at the heart of our profession’s work in the next decades. One of our future stories is as a data profession.
Andrew Cox is a senior lecturer at the Information School, University of Sheffield and led the RDMRose Project. His research interests include virtual community, social media and library responses to technology. He coordinates Sheffield’s MSc in Digital Library Management.
You can follow Andrew on Twitter @iSchoolAndrew
Exploring Research Data Management is an accessible introduction to RDM with engaging tasks for the reader to follow and build their knowledge. It will be useful reading for all students studying librarianship and information management, and librarians who are interested in learning more about RDM and developing Research Data Services in their own institution.
Find out more about the forthcoming book here
Pinfield, S., Cox, A.M., Rutter, S. (2017). Mapping the future of academic libraries: A report for SCONUL. https://sconul.ac.uk/publication/mapping-the-future-of-academic-libraries
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Guest post by Selena Killick, co-author of the forthcoming book Putting Library Assessment Data to Work
With the move to increasing online provision within the education sector, and by association academic libraries, we have seen an explosion in big data sets. The initial COUNTER compliant statistics containing electronic journal title downloads seem quite quaint now as the granularity and scale of data harvesting has continued to expand. It is not uncommon for an academic library to have usage data for its electronic resources at an item level on an individual customer basis. The University of Huddersfield Library Impact Data Project were the first exploration into how library analytics could be used to identify the impact the library was having on student success. The researchers successfully identified a correlation between library usage and student success (Stone & Ramsden 2013). Coincidentally this research was being replicated in Australia and the USA at the same period, all with similar results (Cox & Jantti 2012) (Soria et al. 2013). Five years on, where are we now? And, if data really is the new oil, where should we drill next…?
The Ethical Debate
Before we look at where we could drill next, the question on whether we should drill at all needs to be considered. The librarian field is divided on this issue with strong views on both sides. Quantitative data is not the only source of information and it should not be used in isolation to evaluate library performance. That being said, it is a source of insight available to us and we should consider carefully if and how we use it. Personally, I think that if we are able to use library analytics anonymously, ethically, transparently, legally and with the goal of improving learner success we should exploit the data to benefit our students. I know some will disagree with me, and I’m happy to debate the subject. As data analytics becomes increasing part of the academic institutional infrastructure libraries need to identify the role they will play in this arena or risk becoming obsolete and ultimately redundant.
The Next Drilling Expedition
Until now, library analytics research has focussed on student satisfaction, library usage and student success. The Jisc Library Data Labs project has worked with librarians to combine and visualise various data sets. SCONUL Statistics and National Student Survey (NSS) scores have been combined to see if students who are the most satisfied with library provision are studying at the universities with the largest library budgets (Baylis & Burke 2017). LibQUAL+ satisfaction scores have been combined with Association of College and Research Libraries (ACRL) statistics to see if there is a correlation between satisfaction, usage and expenditure in academic libraries (Hunter & Perret 2011).
As an increasing number of library services move online the ability to harvest and analyse user data in the areas of enquiry handling and information literacy training is growing. Libraries are starting to use customer relationship management systems to manage enquiries received at help points (Killick 2017). Webchat transcripts between customers and librarians can be analysed to identify common enquiries with a view of improving the customer experience (Mungin 2017). Within the area of information literacy training provision, live online tuition and webinars are now being used by academic libraries. Delivery tools such as Adobe Connect can provide the library with data at the individual student level for live attendance and subsequent video views. With regards to data drilling, services are the new content, and it is only a matter of time before someone breaks ground.
Within the wider academic sphere the field of learning analytics has emerged, using big data to understand the characteristics of successful students with a view to optimise the learning environment (Rienties et al. 2017). As an important stakeholder in the learning environment, libraries are considering their role in supporting the learning analytics agenda (Oakleaf et al. 2017). The Library Integration in Institutional Learning Analytics (LIILA) Project is currently reviewing how libraries can support learning analytics. This one-year Institute of Museum and Library Services National Forum grant is working with a variety of international stakeholders, including librarians, system vendors and policy makers. The project team hope to get to the position where libraries are culturally ready and technically able to engage in this arena. This is our opportunity to shape the use of library data in this field, ensuring its use is anonymous, legal, ethical, and transparent; with the goal of improving learner success. If we fail to engage in the debate I suspect our publishers will bypass the library and pipe their usage data to the learning analytics community directly.
Selena Killick is co-author of the forthcoming book Putting LibraryAssessment Data to Work alongside Frankie Wilson. She has presented, published, and provided consultancy services to academic libraries on an international basis on library assessment for over 15 years. She is currently an editorial board member of the International Conference on Performance Measurement in Libraries. In 2003 she was part of the team that introduced LibQUAL+ to the UK in partnership with the Association of Research Libraries. Previously she has worked on the SCONUL Value & Impact Measurement Programme (VAMP) and the SCONUL Statistics e-measures pilot.
You can follow Selena on Twitter @selenakillick
Baylis, L. & Burke, S., 2017. Insights from Jisc & HESA Analytics Labs: An Agile, cross-institutional approach. In 12th International Conference on Performance Measurement in Libraries. Oxford.
Cox, B.L. & Jantti, M., 2012. Capturing business intelligence required for targeted marketing, demonstrating value, and driving process improvement. Library and Information Science Research, 34(4), pp.308–316.
Hunter, B. & Perret, R., 2011. Can Money Buy Happiness? A Statistical Analysis of Predictors for User Satisfaction. The Journal of Academic Librarianship, 37(5), pp.402–408.
Killick, S., 2017. Exploiting customer relationship management analytics to improve the student experience. In 12th International Conference on Performance Measurement in Libraries. Oxford.
Mungin, M., 2017. Stats Don’t Tell the Whole Story: Using Qualitative Data Analysis of Chat Reference Transcripts to Assess and Improve Services. Journal of Library and Information Services in Distance Learning, 11(1–2), pp.25–36.
Oakleaf, M. et al., 2017. Academic Libraries & Institutional Learning Analytics: One Path to Integration. Journal of Academic Librarianship, 43(5), pp.454–461.
Rienties, B. et al., 2017. A review of ten years of implementation and research in aligning learning design with learning analytics at the Open University UK. Interaction Design and Architecture(s) Journal, 33, pp.134–154.
Soria, M.K., Fransen, J. & Nackerud, S., 2013. Library Use and Undergraduate Student Outcomes: New Evidence for Students’ Retention and Academic Success. portal: Libraries and the Academy, 13, pp.147–164.
Stone, G. & Ramsden, B., 2013. Library Impact Data Project: looking for the link between library usage and student attainment. College and Research Libraries, 74(6), pp.546–559.
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Guest post by David Haynes, author of Metadata for Information Management and Retrieval, 2nd edition: Understanding metadata and its use
Use of metadata by the security services
“Metadata tells you everything about somebody’s life. If you have enough metadata you don’t really need content” (Schneier 2015, p.23)
If anyone wondered about the importance of metadata, this quote by Stuart Baker of the US National Security Agency should leave no-one in any doubt. The Snowden revelations about the routine gathering of metadata about international telephone calls to or from the United States continues to have repercussions today (Greenwald 2013). Indeed Privacy International (2017) has identified the following types of metadata that is gathered or could be gathered by security agencies:
- Device used
- Length of call
“Metadata in aggregate is content” as Jacob Appelbaum observed when the Wikileaks controversy first blew up (Democracy Now 2013). In other words when metadata from different sources is aggregated it can be used to reconstruct the information content of individual communications.
Invasion of privacy or personal benefit?
These concerns extend well beyond the use of metadata by Governments and the security services. The social media giants prosper by exploiting personal data and targeting digital advertising. Personal profiles of targeted individuals are based on metadata about online use and are the basis of online behavioural advertising. Cookies and other tracking technologies can monitor the online activity of an individual to predict future behaviour. Metadata about online sessions reveals a great deal about an individual and his or her life. This may extend to gathering information about friends, family, colleagues and other contacts.
The upside of this is that metadata is a powerful tool to facilitate use of online services, by remembering users’ preferences and delivering content that is more likely to be of interest or relevance to them. This has to be balanced against the risks associated with online disclosure of personal data.
Metadata describes an information object whether that be raw data or more descriptive information about an individual. This is important because the treatment of metadata has become a political issue. Personal data, especially data that reveals opinions, attitudes and beliefs is potentially very sensitive. Use of this personal data by service providers or by third parties can expose users to risks such as nuisance from unwanted ads, harassment from internet trolls or fraud through identity theft, if the data is not held or transmitted security. Many digital advertisers would say that because the data is aggregated it is not possible to identify individuals – i.e. the data is anonymised. However this is no protection against privacy breaches as has been demonstrated by Narayanan and Shmatikov (2009) and others.
Daniel Rosenberg (2013) makes a nice distinction between data, facts and evidence. Data if true may be a fact, but if false ceases to be a fact. Samuel Arbesman (2012) in his book ‘The Half Life of Facts’ introduced the idea that in a given period half the certainties that we had are shown to be false or are superceded by new understandings and that they cease to be ‘facts’. Data, whether it is true or not, continues to be data, but is only factual if true. Perhaps there is some way of recording the reliability of information or data so that it can be exploited appropriately. Many of the arguments and counter-arguments on climate change for instance centre on the quality and veracity of the evidence used by each side of the debate. This idea is not new, as medical researchers have for some time evaluated the quality of research used to make clinical decisions. This information about the quality and reliability of data is metadata.
Metadata is political
Metadata has become a political issue because of its use by security agencies and because of wider privacy issues in the commercial world. Anyone who had asked the question ‘What does metadata matter?’ prior to 2013 will realise just how important a bearing it has on current political issues. The Fourth Amendment to the U.S. Constitution protects ‘The right of the people to be secure in their persons, houses, papers, and effects, against unreasonable searches and seizures’ (United States 1791). A lot hangs on the interpretation of privacy as Solove (2011) has so eloquently discussed in his book ‘Nothing to Hide’. ‘Fake news’ is not new, but the phenomenon has reared its head in recent elections and is unlikely to go away any time soon. Good governance also depends on a good understanding of metadata and accountability for past actions.
Metadata for information management and retrieval
In the new edition of Metadata for Information Management and Retrieval, published in January 2018 I consider the origins of metadata and look at the ways in which it is used for managing information resources. The ethical dimensions of metadata are explored and issues such as governance, privacy, security and human rights are considered. The book also discusses the digital divide and the potential that metadata has for making information accessible to wider audiences.
Metadata has an important role in politics and ethics. How then do we manage it to best effect?
Haynes, D (2018) Metadata for Information Management and Retrieval: understanding metadata and its use. ISBN 9781856048248. Facet Publishing. London, 2018, 267pp. http://www.facetpublishing.co.uk/title.php?id=048248
You can follow David on Twitter @JDavidHaynes
Arbesman, S., 2012. The half-life of facts : why everything we know has an expiration date,
Democracy Now, 2013. Court: Gov’t Can Secretly Obtain Email, Twitter Info from Ex-WikiLeaks Volunteer Jacob Appelbaum. Available at: https://www.democracynow.org/2013/2/5/court_govt_can_secretly_obtain_email [Accessed March 21, 2017].
Greenwald, G., 2013. NSA Collecting Phone Records of Millions of Verizon Customers Daily. The Guardian. Available at: http://www.theguardian.com/world/2013/jun/06/nsa-phone-records-verizon-court-order [Accessed July 7, 2014].
Narayanan, A. & Shmatikov, V., 2009. De-anonymizing Social Networks. In 2009 30th IEEE Symposium on Security and Privacy. IEEE, pp. 173–187.
Privacy International, 2017. Privacy 101. Metadata. Available at: https://www.privacyinternational.org/node/53 [Accessed March 23, 2017].
Rosenberg, D., 2013. Data before the Fact. In L. Gitelman, ed. “Raw Data” is an Oxymoron. Cambridge, MA: MIT Press, pp. 15–40.
Schneier, B., 2015. Data and Goliath: the hidden battles to collect your data and control your world, New York, NY: W.W.Norton.
Solove, D.J., 2011. Nothing to Hide: the false tradeoff between privacy and security, New Haven, CT: Yale University Press.
United States, 1791. U.S. Constitution Amendment IV, United States.
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Guest post by the co-authors of The Chief Data Officer’s Playbook, Caroline Carruthers (Group Director of Data Management, Lowell Group) and Peter Jackson (Chief Data Officer, Southern Water).
Being a Chief Data Officer in the current climate is a rather interesting place to be, it can feel a little like dancing on quicksand while you have to learn to juggle wriggling snakes. So in order to help people interested in this area, whether you are a new CDO, well established data hero or just wondering what all the fuss is about, we have worked on a set of articles to answer some of the questions we are asked at nearly every conference we go to. While we can’t promise you a solution to all your data related problems handed to you on a plate, we can promise that once a week you can look forward to another concise, interesting and easy to read article to help you on your data and information related journey.
One of the most difficult tasks for the new CDO is developing a Data Strategy whilst the organisation continues to operate (and must continue to operate) using and abusing data, continuing with bad habits around data and often with a lack of governance and planning. This has been likened to performing open heart surgery on a runner while they are in the middle of a marathon, in reality it’s more like patching them up, giving them water to keep them going and a clear map to get them to the end of the race. In most situations for a new CDO the organisation probably feels that it has been operating quite happily without this new person for a very long while. So, for the new CDO it may feel like they are sitting in the corner talking to themselves. Alternatively the CDO may be met with comments like ‘Yes, we tried that before and it didn’t work’ or ‘ IT/ Finance/ Procurement/ Marketing (delete as appropriate) won’t like you doing that’ or my personal favourite ‘that’s not how we do that here’.
What is the context of Business As Usual? In most cases (unless the organisation is a start-up) it will be:
- a legacy data environment: siloes of data, multiple records, ‘duplicates’, weak data governance, no useful meta data, heavy MI and no BI.
- legacy systems: burning platforms, bespoke developments, hard to maintain and manage, reporting systems remote from end-users, no true data management systems
- legacy business processes: evolved over time, limited by technology and data available at the point in time, containing many work-arounds
- multiple suppliers: of software and systems
- legacy IT department: focused on building stuff rather than delivering and supporting software-as-a-service, internal networks as opposed to cloud
- legacy ‘transformation’ process: based on project governance and waterfall, struggling with agile and innovation. Not able to adapt to transformation being data driven rather than technology driven
The task for the new CDO is how to steer their way through this bubbling cauldron and deliver a data strategy. One approach is to break the task down into two parts: an Immediate Data Strategy (IDS), a tactical approach to deliver support for BAU, gain quick wins and temporary fixes and to prepare the way for the second part. The additional benefit of the IDS is the delivery of incremental value to the organisation through its data, avoiding the hypecycle on the way (the next article deals with this in more detail). The second part is the Target Data Strategy (TDS), the strategic approach. The new CDO cannot sit back and deliver the TDS over a two to three year window, the organisation will probably be expecting some results now, so it is just as important to set realistic expectations as it is to provide some tactical delivery through the IDS. One piece of advice, don’t call these tactical deliveries ‘Projects’ instead refer to them as ‘Initiatives’, this might engender a more agile approach.
The IDS should listen to the organisation’s data pain and try to deliver high profile quick wins. The tactical initiatives of the IDS should blend into the strategy of the TDS, and not run down a rabbit hole or blind alley. The IDS should help build up the narrative and vision of the TDS.
The six key elements of the IDS could be:
- Stability and rationalisation of the existing data environment
- Data culture and governance
- Existing and immediate data and IT development projects
- Data exploitation and integration
- Data performance, quality, integrity, assurance and provenance
- Data security (especially with GDPR in mind).
Whilst the new CDO is delivering the IDS they should be pushing the TDS through business engagement, the organisation needs to be prepared, ready and believe in the changes that are coming. The CDO should also be using the IDS to show the ‘art of the possible’ to a data illiterate business to help the business engage with the new data possibilities. Through the IDS they should be running Proof of Concepts, feasibility studies, data science initiatives and building a narrative around the vision of the TDS for all levels of the business.
Finally, six tips on how to succeed using the IDS and TDS approach:
- Use internal communications to sell the vision, don’t allow a vacuum to form
- Seek every opportunity to communicate the vision. Do not be frightened of becoming a data bore.
- Socialise the data visons and the changes that could be coming, especially the controversial ideas, locate the data champions to support you
- Engage the organisation’s leadership and find your senior sponsors, they will be crucial
- If you can’t explain it, you’re doing something wrong, ‘it’s me not you’
- Win hearts and minds, often a good argument is not enough to win the day.
Facet Publishing are pleased to announce the release of The Chief Data Officer’s Playbook by Caroline Carruthers, Group Director for Data Management, The Lowell Group and Peter Jackson, Chief Data Officer, Southern Water.
Most organisations now accept that data is a fundamental asset but the rapidly evolving role of Chief Data Officer (CDO) is still a mystery to many. Caroline Carruthers and Peter Jackson, two practicing CDOs, unlock these mysteries for the first time in The Chief Data Officers Playbook.
The book is a jargon-free guide for CDOs looking to understand their position better and for aspiring CDOs looking to take the next step in their career. It will also be valuable for chief executives, directors and business leaders needing to understand the value that a CDO can bring to an organisation, what they do, how to recruit one, where they should sit in the organisation and who they should report to.
The authors said,
“Data is a fast-moving and evolving environment and we get the sense that the pace of change is getting faster every month, perhaps every week. Our book is packed with strategies, tools and results of our real-life experiences which can help you leapfrog some of the mistakes we have made and learn from where it went well for us”.
The book begins by explaining why organisations need a CDO before moving on to cover key topics including, what you should do in your first 100 days as a CDO, building your team, how to break the data hoarding mentality, data and information ethics, delivering a data strategy in the context of business as usual, and how to recruit a CDO.
David Mathison, Chairman, CEO and Founder of the CDO Club, said,
“The release of this book is perfectly timed. The CDO Club tracks CDO hires globally, and last year alone the number of new CDO hires quintupled. The Chief Data Officer’s Playbookis a compendium of essential knowledge anyone operating in the current data environment must have”.
Follow the book on LinkedIn for updates and additional content
Browse a free sample chapter on the Facet Publishing website (click on the book’s cover)
Guest blog by the co-authors of The Chief Data Officer’s Playbook, Caroline Carruthers (Group Director of Data Management, Lowell Group) and Peter Jackson (Head of Data, Southern Water).
Gartner predicted that by 2019, 90% of large organisations will have hired a CDO – but only 50% of these will be a success. Much of what determines your success or failure going forward will take place in the first 100 days. Essentially it is about getting the basics right now and building firm foundations for the future.
What do you expect when you start?
The first hundred days are important to set the expectations for the CDO you are going to be going forward; now from one CDO to another, expect a real rollercoaster of a ride, there will be amazing highs followed by moments where you sit with your head in your hands wondering what on earth you have done. Basically a microcosm of the rest of your role as a CDO just crammed into a shorter time period.
Case for change
The very first thing you need to do is understand your organisation’s case for change; if it’s not there, create it; if it needs help, redefine it. But whatever you do make sure you have a clear easy-to-describe case for change. In order to be an effective CDO you will be changing the organisation, and no change starts without a burning platform or an absolutely massive benefit at the end. If you can’t find the case for change then you might as well go home at this point.
What you are aiming for
The case for change helps you set the vision for what benefits you are aiming for, whether they are saving the organisation from repeating mistakes or gaining insight to derive more value. It’s the compelling argument that makes people want to help create the future you are selling. It also helps to set your scope out and start to set expectations about what you will and won’t be doing. People often forget about the ‘not doing’ part of a scope but it’s equally important as what you are doing, if not more so, without it people can overlay their own expectations and just assume they are getting everything they’ve always wanted just because they misinterpreted what you meant. Whilst you need to create a compelling vision, it’s best to be realistic about where you can go, what it will feel like, and how long it is going to take to make a difference.
There is no point in starting a journey without having an idea of your destination. You don’t need a fixed point you are trying to drag the company to, rather an idea in mind of where you are leading them. A bit like giving them a treasure map where you might not have buried the treasure yet but you know what island you are burying it on, they will get more maps the closer to the goal they get.
We are going to assume you have a team in place, knowing how long this process can take, unless we assume you have a team in place the whole story of your first 100 days will be taken up by fighting to get people to come and help you against departments who practice the dark arts and refuse to let you see the play book. There is a need to have people around you to help as no one person will ever be able to change the company without a lot of support. Apart from the need for skills and experience that are varied and wide ranging, you also need the support when you have some of your rollercoaster lows to help you get back on the upward track.
Then you need to look at what basics you are trying to get right, what materials are going to make up your foundation?
To keep it simple we’ve broken these down into three main areas
Let’s face it, you will be making changes to the organisation and you might not always get it right first time – remember the old saying ‘if you never make a mistake you aren’t trying hard enough!’ so what must be in place is a way of letting people know what is expected of them, what are they really accountable for; be that policies, standards, procedures or whatever your company used to help everyone understand their responsibilities, as well as a control mechanism for managing those policies. How do you make decisions on how the organisation needs to treat its data and information? Who is involved in this process? If you are smart you get people involved who cover large parts of your company – the plot for ‘buy in’ starts here.
Next let’s look at your information architecture, not the vast swathes of detail that sit in your data dictionary (at least not at this point) but the big headings. What are the top 5 to 10 ish headings which describe all the information in your company and (most importantly) who is the one person who could make a decision on each one. This is not about playing the blame game, that just makes individuals hide from any kind of accountability and leads to a kind of company wide whack a mole game. Remember the quote from above ‘if you aren’t making mistakes….’ Your information domain owners are accountable experts in their fields who understand specific areas of information within your business and can give firm direction and decisions in their area. Once you have the highest conceptual level agreed then it’s time to move onto the next level, adding richer detail as you go.
Lastly and definitely not least, how are you going to engage with the company? Where is your network of evangelists coming from who will sell your message? It’s great that you know who can make decisions about the information and that you have clear instructions on how people should treat your company’s data but it really is pointless unless you tell them. Naturally we are talking about mass company wide emails that of course everyone reads every detail of, inwardly digests and miraculously and immediately changes their behaviour…….. in our dreams! This is hearts and minds time here, what is your compelling argument to change, how are you making their life better and what is in it for them that makes it worth changing their behaviour? At the very least tell them what you expect from them.
Get all that right and at least you know you have covered off your basics while you start your journey.
The Chief Data Officer’s Playbook will be published in November by Facet Publishing.
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