1. High Level Group for Strategic Directions in Business Architecture in Statistics
Strategic Vision
Gosse van der Veen,
Statistics Netherlands
HLG 2011 Geneva

2. Background
Many separate developments related to modernising statistical production
Groups of ICT specialists and Methodologsts
Not enough power in the groups to make change really happen
Not enough coordination
First, let us start with some background information:
Most international collaboration in the area of information and communication technology (ICT) and the automation of processes and statistical methods has been between specialists. The common objectives have been to share experiences and best practices, and occasionally carry out research and demonstrate innovation. However, collaboration and the common uptake of results in this area have proven to be difficult. The specialists have the power to agree, but miss the authority to initiate substantial changes in their organisations
NEXT 2

3. Background
CES Bureau decided top-level coordination needed: HLG -BAS established in 2010
Create drive from top level management
Information sharing and coordination of developments in CES countries
Advise the Bureau on strategic developments and ensure maximum convergence
To solve this problem it was felt in the CES bureau that an overarching group with coordination power would be beneficial. Such a group should be composed of chief statisticians in order to be powerful enough. In this way we would be able to help the various groups to achieve their aims by supplying ample management support and direction.
We need to understand that for real progress senior and top level management have to step in and drive the changes, actively requesting organisational innovation and show commitment for international cooperation.
A second goal of the group is to keep watch on strategic developments of importance to the statistical community and advise the Bureau on these matters.
In the short history of its existence, the group has come to the understanding that we are running the risk of losing contact with a society that is changing very fast in the very aspects we execute our businesses in: the processing of data into information.
Let me show you a short video to give you a brief illustration of the developments of the last twenty years happening outside our offices.
NEXT
HLG 2011 Geneva

4. Problem Statement
This clip was originally made in 2008 and has, as they say, “gone viral” on the internet. For this presentation it has been shortened considerably.
Lets have a look:
RUN VIDEO
NEXT
2008!!
HLG 2011 Geneva

5. It means that: the sexy job in the next 10 years will be statistician
Hal Varian
Hal Varian is not a random columnist, he is the chief economist of Google and in this role, he is intimately aware of the current developments.
However, I am not completely convinced that he means US.
NEXT
HLG 2011 Geneva

6. Lets add some perspective:
The internet
has 1800
exabytes of
data in 2011
exa = 10^18
What Mr. Varian is aiming at is the fact that we are only slightly aware of the revolution going on around us.
Of course, looking at the graph you will say: “Surely this is not all statistically significant data, maybe only one thousandth part of it might be usable”
Right, so we go from {10 to the power of 18} to {10 to the power of 15}. That is still an incomprehensible amount of data.
And it does not end here:
KLICK (amination)
NEXT
NOW
IDC/EMC white paper 2008
HLG 2011 Geneva

7. We live in exponential times 50.000 EXAbytes in 2020 27 fold growth in
the next
9 years
See?
We will multiply the amount of data in the world by 27 in 9 years.
If there is any answer in turning these amounts of data into information it lies in Methodology and that is an area where we have long traditions of research.
NEXT
HLG 2011 Geneva

8. Paradigm shift
In 1990 data were scarce, interpretation was readily available
In 2011 data are everywhere, interpretation is scarce
We will need of course a lot of different methods to cope with these data masses, our traditional survey toolbox will not help here.
However there is a real need for interpretation of these data and we will have to reconsider our position.
In 1990, there was little data, we had a large part of it in our data centres. Our organisations were quite large, we had ample resources to analyse and to write interesting articles about the things we found.
In 2011 this has changed; our organisations have shrunk, most of the data is outside our data centers. We have to acknowledge that we will not be able to analyse a fraction of this data unless we change our ways.
NEXT
HLG 2011 Geneva

9. An observation: Our product set remains stable
If we look at the past twenty years, our product set has undergone some changes but has in no way reflected the changes going on in the world around us.
We have to reconsider our offering to the public and the goverments supporting us.
NEXT
HLG 2011 Geneva

10. Another observation:
We know little about what is going on at Ebay and other e-commerce sites
Not only is the amount of available data changing into a deluge, also what the public is doing with it is snowballing.
Look at the Auction sites like Ebay, we can only suspect the enormous amount of traffic going on there. A recent report cited for the Netherlands some 9 percent of the gross national product is coming from e-commerce . (by the way, this report was from a private company and financed by Google)
And economic activity that used to be present in the streets is moving to the e-commerce domain.
NEXT
HLG 2011 Geneva

11. For statistical organisations there are new challenges
Hal Varian calls it “Sexy”, Well that might be just about the right attitude to tackle such a challenge
NEXT
HLG 2011 Geneva

12. Product Challenges From surveys to data harvesting
From local to global
From a static product set to a dynamic one
Retain the label “official statistics”
Lets have a closer look at the product side of things:
Doing surveys will turn into a measure of last resort, our respondents are resorting more and more to non response. Besides in the presence of so much data it will be difficult to argue that surveys are needed.
The global perspective is forcing itself upon us, still we also have to maintain our stature as national agencies.
In the area of information processing and hoarding, the world is changing considerably, there will be other things to measure for us and the rate of change will be impressive. We will not be able to maintain the same product set for years.
Lastly I would like to point your attention to our “official status”; There are those that think this official status will protect our monopoly and our livelihood. I do not think that this viewpoint can seriously be upheld for long.
We see lots of others now making statistics we used to be the sole provider of. I do think however, we can see this official status as an enabling feature for us to take advantage of.
NEXT
HLG 2011 Geneva

13. Process Challenges
From artisanal to industrial standardized production
From content matter knowledge to generic methodologies
From IT oriented tools to high level statistical production modules
From achievable quality to negotiated quality
Our processes also bear the hallmark of times gone by. A lot of our workforce is involved in the process of the artisanal production of statistics. In itself there is not so much wrong with it, as was the case in the days before the industrialisation began.
However, others are now beginning to use industrial means (think a few thousand servers in an automated process chain) for the production of statistical figures and we are forced to rethink our position in this. Standardisation on industrial process steps and playing an important role in the standardisation of statistical methods can reinforce our position but will be a challenge.
True statistics mean that you create figures with little content knowledge but with a standard, even generic methodology.
A substantial amount of our workforce is involved in actions that are more inspired by IT knowledge than statistical knowledge, this has to change. For true industrialisation, the tools have to enter the statistical domain and not be in the IT domain.
Quality has to become a property of the product we seek to deliver and be determined as related to the purpose and market of the product. A stable quality for a given product is only achievable by a process of high quality.
NEXT
HLG 2011 Geneva

14. High Level Group Vision:
We have to re-invent our products and processes and adapt to a changed world
Given these challenges we think it is time to act
and to do so as a statistical community.
We have to address these challenges because we have no choice.
The world is changing and we have to adapt.
The High Level Group is proposing this vision to you as a first version on a road to a common understanding troughout the statistical industry. At the end of this presentation I will ask you to participate in the discussion that will lead to a further development of this visoon.
NEXT
HLG 2011 Geneva

15. On Products: Innovate Address the global dimension
In the data and in the products
We need to learn to find data instead of surveying
Procurement and harvesting
The exponential increase of data is the key: we MUST use those data
Let’s begin with our products;
As the global dimension of events gains importance we can no longer work on a national level only and rely on international organisations alone to consolidate. We need to expand our work and deliver products that explain what is happening on a multinational level. In some specific statistical domains, only cross border data makes sense, for example globalisation, enterprise groups and climate change.
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 organisations will have to leave their comfort zone and will have to question the work that seems so normal at present
NEXT 15

16. On Products: Innovate! Take position in the information value chain
Rethink our products related to needs of current society
Who ARE our customers nowadays?
And tomorrow?
Create pockets of innovation
nurture talent and create right conditions
With so much data lying around (literally) we must find ways to make good use of it and develop the opportunities present in those data. We should not wait for other entities to show us how and what!
We must reform and change from people that do surveys in the field to people that do data acquisition or procurement. Nowadays there is a information value chain present and we must take position in it.
We also need to really reassess our productset and rethink our market strategies; true innovation takes nothing for granted
Seeing the challenges, it is clear that the programs of gradual development we have all been running will not deliver the results we seek in the right time. Neither will ambitious master plans aimed at innovating the whole process at once.
Still, innovation is needed badly and we have to find a way to hasten this process. We should create pockets of innovation in our organisations where we bring talent together and enable them to deliver to their maximum ability. Start small; get big.
NEXT
HLG 2011 Geneva

17. On Process: Industrialise
reduce
diversity
Our processes can be industrialised. It will not be in the way Henry Ford changed the world but much subtler. Mr. Ford had no really powerful tools at his disposal, only manpower. His automated factory consisted out of a long chain of people doing simple steps in the process.
Nowadays there are much more sophisticated tools available and industrialisation means a chain of very powerful tools and custom made programs that produce a product in a reproducible way. The human labour is reduced and moved to the design phase where it uses standardised means and methodologies to create a “statistical factory” for a given product.
It is in the design phase that the human knowledge accumulates.
That is what we mean by Common Generic Industrialised Statistics; the blue square. At the moment, to many of our processes reside in the grey area where diversity reigns and artisanal processes are used.
The cornerstones are the GSBPM, The Generic Statistical Business Process Model that is currently under administration of the UNECE, including the change management of it, together with the GSIM, the Generic Statistical Information Model, which is being developed in the Statistical Network and the CORE ESSnet project. In the practical area standardised methods and technology will enable us to rationalise.
If we realise this we can reduce the diversity in methods, IT solutions, business concepts and information concepts and harmonise and standardise our industry.
We here together, are the statistical industry. We will have to work hard to remain so.
NEXT
HLG 2011 Geneva

18. On Process: Industrialise
Four phases:
Product design
Process design
Production
Analysis
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 and take our cue from other industries and see it as a seperate function.
(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.
NEXT
HLG 2011 Geneva 18

19. On Process: Industrialise
Standards save money
New methods for large volumes of data
Minimise labour, innovate
Collaborate, ease the burden
Summarising:
Standardising will save us some of the money we so badly need for developing new methods and processes to cope with the large volumes of data. We also have to lessen the amount of labour involved in production.
However there is a bootstrap problem here, the investments needed will be difficult to realise for most of us.
So, to make this possible we have to collaborate and ease the burden on our organisations.
NEXT
HLG 2011 Geneva

20. Vision: Our Challenges
Create a culture of change, find the talents in our organisations
Use the leverage of our official status
Take position in the information value chain
Process quality through standardisation
Of course It will not be easy to bring all this about. There will be more challenges before we are where we want to be.
We already can see the first set:
Most of us can testify that it is not easy to create a culture of change let alone populate it with talent. Still we have to do so.
The leverage of our official status will not last forever, we have to make good use of it while it is still strong.
The information value chain that is coming into existence is not created for us, we will have to push our way in. Into a chain that is not really waiting for us. Still we have to do so.
Standardisation will mean that we will have to take something from our workforce that they value very highly, some of their freedom to make intelligent decisions about how to do their job
(imagine someone at the Toyota factory changing the outside mirrors to another model all by himself in a running factory! can you hear the customers?)
Still we need to reduce the diversity where it does not pay. It might pay in our product set, but not in our process.
NEXT
HLG 2011 Geneva

21. Conclusion and Pressing Ahead
The world is changing profoundly
We have to adapt or become obsolete
Collaboration and joining forces is vital
This Workshop: answer the HOW question
Concluding we can say that:
The world has changed very much with respect to information processing and information availability and we will have to adapt or risk becoming obsolete. We have to join forces as an industry and solve this predicament
In this workshop we face the task to formulate a strategy for implementation and proposals to get this underway. I envcourage you to think outside the box. Do not assume that things will remain the same. Success!
NEXT
HLG 2011 Geneva

22. Thank You
HLG 2011 Geneva