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Summary

In 2010 the Bureau of the Conference of European Statisticians created the High-Level Group for Strategic Developments in Business Architecture in Statistics (now called the High-Level Group for the Modernisation of Statistical Production and Services), comprising heads of several national and international statistical organizations, to reflect on and guide strategic developments in the ways in which official statistics are produced. The High-Level Group has developed a vision paper to provide the necessary coordination and strategic direction to the many international initiatives currently working on related topics. This vision paper is presented to the Conference of European Statisticians to inform delegates, and seek their feedback and support.

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I. Introduction

A. The product challenge

1. Traditionally the output of statistical organizations has been determined by the demands of their respective governments and other organizations. The process is one of reasoning back from the output desired to survey design. This approach was mostly caused by the fact that little or no data were available. This has shaped the way official statistics are designed and produced. We have elaborate coding schemes like the International Standard Industrial Classification (ISIC) on which we have based carefully designed surveys. Gradually - and somewhat reluctantly at first - we have included the use of official registrations in our daily work. We determine which registrations would be able to fit our pre-specified needs, then try to process and edit them to replace or supplement survey data.

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3. The experience at Statistics Netherlands with the household expenditure survey shows that the way we used to produce statistics may become outdated soon: People in the survey keep track of their daily spending in a small book for a month or so, which is then processed into statistics on household spending. While it was feasible to ask people to do this 10 or 20 years ago, the dynamics of current society are such that:

(a) People are conducting many more transactions daily;

(b) They have less patience with statistical organizations amidst all kind of commercial surveys and television shows that draw their attention;

(c) Representativness is becoming problematic because some groups in society are not willing to cooperate at all.

4. In the future it will prove to be unrealistic to expect meaningful figures from this approach, even when results are collected and transmitted electronically. This is a typical statistical product from a past era, when this was the only way to get at these data.

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7. In an information society there is an abundance of data. To a statistical organization this represents an abundance of opportunities. We have to learn to look in this way at the available data and find the opportunities hidden in there and not only see them as ore for our stovepipes which have to be refined to fulfil our predefined needs.

B. The process challenge

8. The changes in our society increase the need for more and quicker statistics. Quality is negotiable but needs to be communicated. The challenge for statistical organizations is to be sufficiently flexible and agile to provide statistics according to user needs, at an acceptable cost. Statistical organizations are starting to acknowledge that it is becoming too expensive for each and every one of them to individually change their tailored production systems to meet user expectations.

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12. For real progress senior and top level management have to step in and drive the changes, actively request organizational innovation and show commitment for international cooperation.

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II. Vision

13. The High-level Group for Strategic Developments in Business Architecture in Statistics (HLG-BAS) has been established to add power and governance to the various groups working under the umbrella of the Conference of European Statisticians, and other groups working in the area of modernising statistical production. It provides top management ownership and coherence. As a first step the HLG-BAS is defining a strategic vision, which will also serve as a means of alignment for the groups.

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15. We need to define our strategy in two directions:

(a) Statistical output: New and better products and services more tuned to the way the world is operating today, and created from a global perspective. This will help us to stay relevant;

(b) Production methods: Different and better processes and methods tuned to delivering our products at minimal cost with greater flexibility and in cooperation between institutions. This will help us to improve efficiency and effectiveness.

A. On products

16. Statistics can be a most exciting business, showing causality where there was none expected and providing insight into the inner workings of our society. It used to be very difficult to fulfil that role, data being scarce and expensive; a survey is a costly instrument. In a society that is transforming into an information society, we can be an exciting business. Data are everywhere and are much cheaper than they used to be. Slowly people are beginning to understand the real value of this fact. For example, although they did not start out as such, social networking sites and search engines are now perceived as data collection devices. We, as impartial organizations with legislation on our side, are in a unique position to connect to the data of the emerging information society and transform them into something useful.

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18. The raw materials, the data we use to create our products, will need to be found in the data that are already available throughout society. The opportunities these data represent will need to be transformed into concrete statistical products. The active pursuit of data and the creation of products that give insight from an impartial perspective, our unique selling point, will be our new mission. It will undoubtedly mean that our organizations will have to leave their comfort zone and will have to question the work that seems so normal at present.

B. On processes

19. The production of statistics should be based on common and standardised processes, transforming raw data into statistical products according to generic and commonly accepted information concepts. In some cases, standardisation of processes and the availability of international data sources could lead to statistical production at a multi-national level, for example perhaps price statistics could be produced in a single production process for more than one country. Similar examples could be envisaged for processes using data from aerial-surveys or remote-sensing techniques. International agreements and uptake of these principles should lead to increased harmonisation of production methods, and subsequently extend the market potential for common production means and solutions provided for by the statistical community or the commercial information and communications technology industry.

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21. Each statistical organization is a factory of statistical information. Together these statistical organizations form the 'official information' industry. Like any established industry, the production of official statistical information should have its own industrial standards. On the one hand, this will provide a necessary foundation for development and exchange of the means of production among the statistics producers, and potentially create a market of commercial interest to our benefits. On the other hand, this will consolidate the use of our statistical outputs in the global information community, making them readily accessible, interpretable and comparable.

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III. The road to new statistical products

22. Key to a new understanding of our profession is the fact that the changeover to an information society will cause a profound change in our business.

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25. We believe that the amount of available data is one of the key factors. These data have to be actively hunted for and their possibilities researched. We need to assess whether this is a viable direction for our trade before we think about full commitment. For the coming year we propose to delve deeper into the opportunities we perceive and thus demonstrate their added value.

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IV. The road to industrialisation and standardisation

26. The strategic goal of industrialisation is a complex set of prerequisites that must be aligned and converged.

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36. The increased cost effectiveness represented by the industrialisation of statistics should be realised by dividing the whole process in four phases:

(a) Product design; we need to start designing statistical products with manufacturability as a prominent constraint;

(b) Process design; the statistical production process (manual and automated) should be designed using methods and logistics that are modular in nature and exchangeable between organizations, and as independent as possible from subject matter constraints;

(c) Production: the statistical process should be executed by machines, with as little human intervention as possible, and with short turnaround times (close to real time should be possible). Key is the minimisation of operational costs;

(d) Analysis: Statistical subject-matter specialists should use outputs and intermediate results to publish articles and do research with advanced tools and as little human intervention as possible.

37. Although production and analysis will have to be carried out by each organization, design should be done in collaboration between organizations, and enterprise architectures will need to be aligned. For this all to become reality, things will have to change.

38. The change is urgently needed. The demands of modern society are completely different from what they used to be 20 years ago and we risk becoming obsolete. Although our organizations have a reputation to uphold for producing statistics of indisputable quality, which inevitably implies a time lag. We need not impose our own planning upon the world; our figures should be ready as soon as our sources have delivered.

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V. Challenges

A. Energise innovation

39. We need to establish a culture for change. Among our most important assets are our human resources. That is where we keep our knowledge and our culture. In most organizations there is a good supply of forward thinking people. The challenge is to unlock this potential. We should encourage an entrepreneurial attitude and look for ways to change the culture in our organizations where necessary.

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44. Being part of an information network must become part of our culture. Instead of being self-contained and self-sufficient as a statistical system, we must realise that we are becoming part of a more complicated network of data providers and information producers. We need to be aware of the processes that create the data we are interested in. This means that we must take a place at the negotiations table on numerous occasions to fight for our position in the value chain of information producers. We must show our added value as professionals in statistical data processing.

B. Standardise to improve latitude

45. Standardisation is an enabler for change. The objectives of standardisation are to gain efficiency, to be able to automate processes and to prepare for added value of various kinds. Through standardisation we can re-allocate resources, change the focus from production to products and become more agile to respond to the needs of our users and societies.

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47. Protect and govern your profits. Standardisation is not a goal in itself, and can not be driven irrespectively of well defined business cases. Accordingly, when reaching the objectives, the profit from successes must be captured and re-allocated.

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VI. Conclusion and pressing forward

48. The changes we are proposing are profound and it will be a challenge to achieve them, but the world in which we used to define our role in no longer exists. For us, as statistical organizations, there is no other way forward than to adapt and to create an advantage (again). This will take a lot of time and effort, and we will have to collaborate to retain the relevance we need. But then, our world is changing and we have to change with it.

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50. We, the HLG-BAS, seek your commitment to implement this vision in the coming decade and together create a statistical industry that can keep up and even be ahead of its time.

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[1] Developed by the Conference of European Statisticians Steering Group on Statistical Metadata - see www.unece.org/stats/gsbpm
[2] To be developed in cooperation between various international groups including the Statistical Network and the CORE (Common Reference Environment) project.

 

 

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