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COVID-19: Numbers have meaning

COVID-19: Numbers have meaning

COVID-19: Numbers have meaning

One of the benefits of data that is compliant with ISO 8000 is that the data is exchangeable without loss of meaning. For those of us involved in data quality, the current flurry of data published about the COVID-19 pandemic is throwing up some familiar failings.

The media is taking lots of data from various sources and turning it into information in an effort to help the general public understand what is happening. However, a number of media outlets are not reporting the definition of a particular figure accurately. As an example, the identical single figure for deaths is being reported in the same publications as being both “from” COVID-19, and “with” COVID-19. Two entirely different concepts.

When this pandemic is over there will be lots of people trying to make sense of the data. One of the likely measures will be deaths per 1m of the population. Comparing total deaths to a fixed measure of the population will give a better sense of the effects than simply using the figure for total deaths by itself.

This article is not attempting to analyse the current data. The purpose of the article is to explain why looking at a single figure and drawing conclusions is not giving the complete picture, why understanding the definitions behind each data element is important, and, in the case of England and Wales, how the data is collected.

Is the data fit for purpose?

Fortunately, in England and Wales the Office of National Statistics (ONS) follows good practice.

In data standards we talk about the quality of data being defined as its “fitness for purpose”. More specifically in the case of ONS data, it is the fitness for purpose with regards to the European Statistical System dimensions of quality:

  • relevance – the degree to which a statistical product meets user needs in terms of content and coverage;
  • accuracy and reliability – how close the estimated value in the output is to the true result;
  • timeliness and punctuality: the time between the date of publication and the date to which the data refers, and the time between the actual publication and the planned publication of a statistic;
  • accessibility and clarity – the ease with which users can access data, and the quality and sufficiency of metadata, illustrations and accompanying advice:
  • coherence and comparability – the degree to which data derived from different sources or methods, but that refers to the same topic, is similar, and the degree to which data can be compared over time and domain, for example, geographic level;

and two other important dimensions:

  • output quality trade-offs; and
  • assessment of user needs and perceptions.

The ONS issues comprehensive data sets free of charge so that detailed analysis can be carried out by third parties.

How the ONS report deaths in England and Wales

The ONS produce summary information on annual deaths. The following table lists the number of deaths each year in England and Wales between 2014 and 2018.

The general rise in these figures is something to bear in mind when reviewing the average number of deaths during this period when compared to the five-year average, and is another reason why using the number of deaths per million gives better context to the figures. According to the ONS, the population of England and Wales in mid-2014 was 57,408,600, and in mid-2018 it was 59,115,809, an increase of 1,707,209. When the mid-2018 data set was published, the ONS noted that “Since mid-2000, the population of the UK has grown by almost 7.5 million and there are 2.4 million more people aged 65 to 84 years and 489,000 more aged 85 years or over.” Annual population updates are normally published by the ONS in the last week of June.

The ONS also records “excess winter deaths”. In the 2018 to 2019 winter period (December to March), there were an estimated 23,200 EWD in England and Wales. This was substantially lower than the 49,410 EWD observed in the 2017 to 2018 winter and lower than all recent years since 2013 to 2014 when there were 17,280 EWD.

How the ONS is reporting deaths involving COVID-19

As a result of the current pandemic, the ONS currently provides a separate breakdown of the numbers of deaths involving COVID-19. That is, where COVID-19 or suspected COVID-19 was mentioned anywhere on the death certificate, including in combination with other health conditions. If a death mentions COVID-19, it will not always be the main cause of death, it will sometimes be a contributary factor. The conditions mentioned on the death certificate are used to derive an underlying cause of death.

Mortality statistics in England and Wales are derived from the registration of deaths certified by a doctor or a coroner. Deriving conditions from a death certificate introduces a known variable; the accuracy of the data drawn from the certificate is dependent on the doctor completing the certificate. Before submitting a death registration through the Registration Online (RON) system, the registrar will verify that all the information provided has been entered accurately. There are some automatic validation checks within RON to help the registrar with this process. The cause of death reported represents the final underlying cause of death. This takes account of additional information received from medical practitioners or coroners after the death has been registered.

The authoritative source in England and Wales for the certification of births, marriages, and deaths is the General Register Office (GRO). The GRO pass death registration information to the ONS electronically, and the ONS: codes; compiles; and publishes these figures weekly.

The ONS short list for cause of death is based on a standard tabulation list developed in consultation with the Department of Health. This list of over 100 conditions was based on the following:

  • all conditions given in the World Health Organization (WHO) basic tabulation list; with the exception of a few conditions that are so rare as certified causes of death in England and Wales that they could safely be excluded from the list;
  • totals for each International Classification of Diseases, Tenth Revision (ICD-10) chapter;
  • conditions used in monitoring public health targets;
  • other conditions often cited by ONS.

Currently, in the UK The Department of Health and Social Care (DHSC) release daily updates on the GOV.UK website counting the total number of deaths reported to them that have occurred in hospitals among patients who have tested positive for the coronavirus (COVID-19) up until 5pm the day before.

Since 2 April, NHS England have been releasing daily updates of deaths in hospitals among patients who have tested positive for COVID-19 in England, which includes updates on previous days numbers.

The Office for National Statistics (ONS) provides figures based on all deaths registered involving COVID-19 according to death certification, whether in or out of hospital settings.

At the time of publication, further work is in progress across government to reconcile all sources of COVID-19 deaths data, but as you can see these figures are not directly comparable.

The figures produced by the ONS are about two to three weeks behind the daily reported deaths.

There has been a lot of speculation regarding the number of deaths in care homes. The ONS publishes this data.

There has also been speculation regarding whether influenza and pneumonia deaths are recorded each year. They are:

One point to note here is that the reporting of deaths involving COVID-19 is more comprehensive than the previous reporting of respiratory infections, so any comparison of these figures should make this point.

The England and Wales ONS is very clear on how it compiles the information it publishes. Authoritative data sources are always the best places to go start your search for data. Authoritative sources are normally very clear about the definitions for the data they publish, and very open about the methodologies they use. I was visiting the Korean Data Agency in Seoul at the start of this outbreak, and saw first hand how they operate. The ONS is very open, their website (www.ons.gov.uk) is a mine of useful information, and much of the text in this article describing how the numbers have been derived has been drawn from various parts of that site.

Social statisticians studying this mortality figures from pandemic will have lots of data to analyse in the future. They will also look at comparing population density rates as well as the number of deaths per million. They will also adjust the figures for the variability of testing – in both quantity and quality of the tests. The total mortality figures you read about now will have more context in the future.

How is COVID-19 data recorded where you are?

I would be very interested to hear from my fellow data experts in other countries, as to how their deaths are being recorded and published by their data agencies, and if their officially published figures for COVID-19 include deaths “involving COVID-19” where COVID-19 is not the main cause of death. Looking at the deaths per million of population figures published to date, there are some interesting variances that may be explained by the way the data is collected.

When the data is analysed in the coming years, we will need detailed quality data with clear definitions. There will be lots of variances, certain types of deaths will rise, others will fall. We will need to make sure we are comparing like numbers before we draw conclusions. This is vital to enable accurate decisions to be made about managing, or even preventing future pandemics.

About the author

Peter Eales is a subject matter expert on MRO (maintenance, repair, and operations) material management and industrial data quality. Peter is an experienced consultant, trainer, writer, and speaker on these subjects. Peter is recognised by BSI and ISO as an expert in the subject of industrial data. Peter is a member ISO/TC 184/SC 4/WG 13, the ISO standards development committee that develops standards for industrial data and industrial interfaces, ISO 8000, ISO 29002, and ISO 22745. Peter is the project leader for edition 2 of ISO 29002 due to be published in late 2020. Peter is also a committee member of ISO/TC 184/WG 6 that published the standard for Asset intensive industry Interoperability, ISO 18101.

Peter has previously held positions as the global technical authority for materials management at a global EPC, and as the global subject matter expert for master data at a major oil and gas owner/operator. Peter is currently chief executive of MRO Insyte, and chairman of KOIOS Master Data.

KOIOS Master Data is a world-leading cloud MDM solution enabling ISO 8000 compliant data exchange

MRO Insyte is an MRO consultancy advising organizations in all aspects of materials management

What is K:spir and how can it revolutionize the SPIR process?

What is K:spir and how can it revolutionize the SPIR process?

What is K:spir and how can it revolutionize the SPIR process?

The SPIR process urgently needs to enter the 21st century

At KOIOS Master Data we have a unique understanding of the difficulties caused by the current SPIR (Spare Parts Interchangeability Record) process. Through our team’s years of MRO consultancy work, we have first-hand experience of how damaging the poor-quality data supplied in SPIRs can be to oil and gas projects. It can have a profound effect on cost, time and resource – cost, time and resource that could be spent innovating and developing a competitive advantage. Not to mention, the unnecessary wastage it can lead to, in an industry that can hardly accommodate it in the current climate. In this age of Industry 4.0, digital transformation and international data standards such as ISO 8000, the question begs – why is data quality consistently letting the side down? When we struggled to find an effective SPIR solution, KOIOS Master Data was born and we set out to create one.

K:spir is the only SPIR software designed this century using ISO 8000 standard data. It creates machine-readable data that retains quality throughout the chain, enabling accurate decision making and resulting in reduced cost, time and resource.

Here, we look at the importance of master data management, the challenges created by the SPIR process, and how K:spir is uniquely positioned to resolve those challenges.

Why is data management so important to the SPIR process?

In this age of ‘data explosion’, most businesses are aware of how poorly-managed data can put them on the back foot. In Experian’s 2019 Global Management Data Research, they found that 95% of organizations surveyed see a negative impact from poor data quality.

Similarly, the Aberdeen Group’s Big Data Survey in 2017 found that the biggest challenges for Executives arise from data disparity, including inaccessible data, poor quality data informing decisions and the growing need for faster analysis. 

The overall effect is a lack of trust in data, to the great detriment of strategic decision making. And when you can’t trust your data to inform business decisions, then cost, time and resource will inevitably suffer.

In the context of the SPIR process, accurate decision making is everything. The SPIR exists as a tool for forecasting spares requirements for the life of a project, its sole purpose being to assist the Owner Operator (O/O) to make accurate decisions. Yet, as many will attest, the data supplied is often inaccurate, hard to access and sometimes supplied by the Engineering Procurement Contractor (EPC) at handover, by which time it is often too late to inform anything at all. 

Experts have raised the question – if you can’t trust SPIRs to make accurate procurement decisions, then are they worth the paper they’re written on?. The process is clearly out-of-date, yet it continues to blight the efficiency of many oil and gas upstream projects.

SPIRs dissected 

The shortcomings of the antiquated SPIR process can be summarised into three key areas:

1. DATA IS INACCURATE AND OVER-SIMPLIFIED

SPIRs are generated from paper forms and are transcribed many times, so part descriptions become distorted. Often, parts have multiple descriptions.

Solution: K:spir locks in data quality right at the start of the process, using ISO 8000 standard data. Part descriptions are consistent and safe from misinterpretation, providing confidence in forecasting and reordering. 

SPIRs are usually completed by an Original Equipment Contractor (OEM), who is not necessarily aware of the O/O’s operating and maintenance procedures. Therefore, they do not take into account equipment criticality or maintenance capability.

Solution: K:spir uses the maintenance and repair strategy to determine the spares requirement, reducing wastage and taking cost off of the bottom line.

2. DATA IS INACCESSIBLE AND DIFFICULT TO ANALYZE

SPIRs often provide information in spreadsheets or pdfs, which are impossible to extract data from quickly, if at all. To extract anything meaningful is very cost and time-intensive, and relies on support from IT specialists.

Solution: K:spir provides instant reporting on the completeness and cost of spares, allowing for accurate decision making. The information is fully configurable to the requirements of the O/O. It can also create a Maintenance Bill of Materials (BoM) and is interoperable with maintenance systems.

Information is not portable and has to be re-entered for different systems.

Solution: K:spir generates portable (machine-readable) data saving significant time spent re-keying information and unnecessary data handling costs.

Data exists on many platforms and is not available to all stakeholders, all of the time.

Solution: K:spir is cloud-based, providing simultaneous access to all stakeholders in the chain. This allows for more transparency and accountability at all stages of the project lifecycle.

3. DATA IS SUPPLIED TOO LATE

Sometimes even as late as handover, by which time it’s too late for the O/O to minimize the operating risk. There is no opportunity to make informed decisions, such as ordering spares with long lead times, or calculating warehouse space. This can lead to unnecessary wastage and operational difficulties along the line.

Solution: K:spir provides transparency right from the beginning of the project, allowing for critical decisions to be made early on. 

With its unique set of features and benefits, it’s clear that K:spir can relieve the symptoms of the current SPIR process with immediate effect, saving valuable cost, time and resource.

A SPIR – this is not what efficiency looks like!

SPIRs and effective MDM – who is responsible for getting it right?

As confident as we are in the KOIOS software suite to advance the world of Master Data Management (MDM), there are clearly other factors that need to be addressed, most notably, ownership. It is a thorny area, and one that is being more keenly contested as digital transformation rattles on apace. As the Aberdeen Group puts it, there is a “growing urgency for better data management”, as businesses see the shortfalls of their inability to harness data. 

Experian’s report shows that in 84% of cases, data is still managed primarily by IT departments. Revealingly, 75% of their sample thought that ownership should lie within the business, with support from IT. They conclude that organizations should develop their MDM strategy to fulfill the needs of a much larger group of stakeholders, who wish to harness the power of their data to improve decision making and efficiency.

In the context of SPIRs and oil and gas projects, we believe that O/Os should become more demanding over the quality of data supplied to them by manufacturers. It is unrealistic for their IT experts to have sight of the broader operational requirements, with their own priorities being diverse and demanding. It is the Executives who suffer the consequences of the risk taken by ignoring poor data, and the operations and maintenance departments that will experience the pain. Clearly, they need to make their voices heard much earlier in the process. That said, manufacturers and EPCs also need a better understanding of the challenges faced by O/Os, and in our view should share the responsibility for getting the data right from the start.

It is, as previously stated, a tough subject, but we are constantly encouraged by the conversations we have with manufacturers and O/Os alike. More and more key stakeholders are waking up to the power that effective MDM can have in driving business forwards, by freeing up cost, time and resource and supporting strategic decision making. Not just to their own ends, but for industry as a whole to fully realize its digital transformation goals.

Join us in our vision to revolutionize the SPIR process

A radical change to the SPIR process and MDM as a whole is on the horizon. While there may be no silver bullet, we firmly believe that the right software is an essential move forward. The KOIOS software suite is geared towards this larger shift in MDM, but in the case of K:spir, the results can be felt immediately.

Our hope is that O/O’s and manufacturers alike will unite in becoming more discerning and demanding about data quality, working as one to create harmony along the chain. At KOIOS Master Data, we are committed to leading the conversation and driving better data quality.

Contact us

If you wish to become part of the change and join us in our vision to revolutionize the SPIR process, we would love to discuss it further with you. 

+44 (0)23 9387 7599

info@koiosmasterdata.com

Manufacturers will welcome the introduction of ISO 8000-115

Manufacturers will welcome the introduction of ISO 8000-115

Manufacturers are increasingly concerned about how their master data is being represented on various websites, web stores, and in the systems of distributors and product end-users. Organizations collect master data from other organizations and reference and manage that data in their own systems in order to perform transactions; so, who owns that master data?

The global data quality standard, ISO 8000 is helping to resolve these issues.  The creation of a computer readable and portable product specification has been covered by ISO 8000-110 for a number of years now, but this month sees the publication of ISO 8000-115 covering identifiers.

Manufacturers will welcome the introduction of ISO 8000-115

The introduction of ISO 8000-115 asserts the manufacturer’s intellectual property rights to the product specifications they produce.

Most commonly an identifier is a reference to a data set managed by the owner of the identifier and, as such, it is an alias for a master data record.  Identifiers are widely exchanged by governments and commercial companies to refer to data used to describe individuals, organizations, locations, goods, services, assets, processes, procedures, laws, rules and regulations.

Identifiers play a crucial role in supply chain management and product lifecycle support as they identify physical objects using serial numbers and asset tracking numbers, and items of production using model and part numbers.

Verifying and validating the quality of master data depends on an ability to identify the owner of data and any use restrictions on that data.  This verification and validation also requires an ability to resolve identifiers to the data sets that they identify.

Part numbers are often designed to include some form of classification and often contain coded characteristics of the item. While part numbers are not necessarily unique, it is not unusual for companies to use part or model numbers as brands.

Several initiatives have been developed designed to create universal part numbers.  Most of these consist in adding a prefix that uniquely identifies the manufacturer or supplier who issued the number. The most common are bar codes such as the Universal Product Code (UPC) or its replacement, the Global Trade Identification Number (GTIN), issued by GS1, formerly a joint effort between the US Uniform Code Council (UCC) and European Article Number (EAN) International. The basic principal of the UCC/EAN UPC and GTIN numbers is central control of globally unique manufacturer or supplier prefixes associated with an understanding that the manufacturer or supplier controlled suffix should be unique to that manufacturer or supplier.

There are a number of drawbacks to GTINs for industrial users.  The copyright owner of the GTIN is GS1, not the owner of the product; the product owner is identified only by a numerical prefix element in the code, so is not obvious to any user; barcodes relate to the package, so one item may have more than one barcode depending on how it is packaged, a useful feature for retail, but not for industrial product end-users; barcode numbers can be reissued, so again in industrial settings where products have a much longer life-cycle, this may cause issues.

The Amazon Standard Identification Number (ASIN) may also face similar issues as Amazon expand their operations into Amazon Business.

ISO 8000-115 is significant because it specifies the requirements for the quality identifiers that form part of an exchange of master data. These requirements supplement those of ISO 8000-110.

ISO 8000-115 is significant

… because it specifies the requirements for the quality identifiers that form part of an exchange of master data. These requirements supplement those of ISO 8000-110.

Verification and validation of master data requires an ability to resolve identifiers to the data sets that they identify.  ISO 8000-115 compliant identifiers have a clear structure for prefix and identifier elements that are both human readable and electronically resolvable, and most importantly, the prefix element clearly identifies the owner of the master data.

ISO 8000 asserts that master data identifies and describes individuals, organizations, locations, goods, services, processes, rules and regulations.  That covers most of the master data that organizations manage.

Characteristics that define master data quality include syntax, semantic encoding, conformance to requirements, provenance, accuracy, completeness, and data governance. The 100 series of ISO 8000 specify the characteristics of master data messages that are generally needed to ensure reliable communication of information between a sender and a receiver.

Data that is factual has no copyright protection under U.S. law; it is not possible to copyright facts. In many cases, an individual data element in a data management system as well as the metadata describing that data will be factual, and hence not protected by copyright.

Information, however, is intellectual property.  Relating different data elements into a specification is a creative decision that may receive copyright protection.  A data element, such as a property value pair, in a specification, for instance the bore size for a bearing is factual.  A series of facts assembled into the specification can be considered a creative decision, and the assembly of the data elements therefore, information.

Collecting information using researchers (or data cleaners) does not give you intellectual property rights to that information.

Next steps for manufacturers, distributors and product end-users

Manufacturers will welcome the introduction of ISO 8000-115 as it asserts their intellectual property rights to the specifications they produce.

  • If you are a manufacturer, you should be checking your PIM or cataloguing system to see if is compliant with ISO 8000-110 and ISO 8000-115.
  • If you are a distributor you should be asking the manufacturers you distribute for to supply ISO 8000-100 compliant specifications for all the products you distribute.
  • If you are a product end-user you should be asking your suppliers, be they EPCs, OEMs, distributors, or parts manufacturers to supply you with ISO 8000-110 compliant specifications for the products you buy, then, in combination with the ISO 8000-115 identifier you can now verify and validate the product data and its provenance.

 

Author: Peter Eales, MRO Instye Limited

Peter is a member of the ISO working group for ISO 8000 and is registered as an industrial data expert with ISO.

 

The new paradigm for managing product master data

The new paradigm for managing product master data

The management of product master data is having a revolution. The excellent data quality standards ISO 22745 and ISO 8000 from the International Organization for Standardization (ISO) in Geneva, Switzerland,  have changed everything.

In order to adapt organisations need to adopt a new mindset, new tools, new processes, and importantly, people need education and training. Getting this right will lead to significant productivity improvements and an array of other benefits that include: more accurate ordering and a reduction in purchase errors, less operational downtime hunting for the source of supply for spares, greater detail and consistency of product data on eCommerce web sites, shared product specifications throughout the supply chain, less exposure to fraud and counterfeiting through the use of authorized legal identifiers and many more.

Data cleaning is now dead, as is the use of noun-modifiers to define product specifications. Cataloguing at source is the new paradigm. The best entity to describe a product is the manufacturer who designs and builds it, and their product data should be used throughout the supply chain. Doing so means everyone in the supply chain can share the correct product data; load it into their ERP, eCommerce, and/or Punch-out systems; order the right parts from the right supplier at the right time; and cut out expensive, and often inaccurate, data cleaning work. It means purchasing errors are significantly reduced, or eliminated entirely, and the risk of downtime whilst spares are sourced minimized.

The charts below lays out the key success factors organisations need to implement in order to benefit fully . Find out more at www.koiosmasterdata.com