Will You Successfully Defend Your Business against Invading Spreadsheets?

When we at Product Data Lake are exhibiting on trade shows (yes, we sadly are that old school, sometimes), we have a computer game called PDL Invaders. The game is built over the legendary computer game called Space Invaders. In our version, you use the PDL spaceship to shoot down invading spreadsheets and emails.

TFM16The purpose of the game is to emphasize one of the main reasons of being for Product Data Lake. We want to replace the use of spreadsheets for exchanging product information in cross company supply chains with our automated cloud service.

Spreadsheets is the most common tool to directly exchange product information between trading partners today. The typical scenario is that a receiver of product information, being a downstream distributor, retailer or large end user, will have a spreadsheet for each product group that is emailed to be filled by each supplier each time a new range of products is to be on-boarded (and potentially each time you need a new piece of information). As a provider of product information, being a manufacturer or upstream distributor, you will receive a different spreadsheet to be filled from each trading partner each time you are to deliver a new range of products (and potentially each time they need a new piece of information).

Customer data portals is a concept a provider of product information may have, plan to have or dream about. The idea is that each downstream trading partner can go to your customer data portal, structured in your way and format, when they need product information from you. Your trading partner will then only have to deal with your customer data portal – and the crowd of other customer data portals in their supplier range. Add to that, that spreadsheets is the “natural” tool to download data from such a portal.

Supplier data portals is a concept a receiver of product information may have, plan to have or dream about. The idea is that each upstream trading partner can go to your supplier data portal, structured in your way and format, when they have to deliver product information to you. Your trading partner will then only have to deal with your supplier data portal – and the heaps of other supplier data portals in their business-to-business customer range. Add to that, that spreadsheets is the “natural” tool to upload data to such a portal.

Product Data Lake is the sound alternative to the above options. Hailstorms of spreadsheets does not work.

Follow us on LinkedIn and get up to date information about when the PDL Invaders game will be close to you. Our company page is here.

 

Data Management, Never stop learning

Welcome in the class room to Rick Buijserd from The Netherlands as the next guest blog post author:

class-romm

As a child you were happy when the bell ranged and the school day ended.  It was time to play with your friends and don’t think about learning anymore, just play! Most of us look back at this time as the best time of our lives. A time without any worries and enjoying every moment of it. Even though it wasn’t the main focus as a child it was also the time that we learned new ideas and things every day. Are we still learning every day? Are you learning new things about data management every day? You should and here is why…

Gaining knowledge

Data is the new oil and many of us make a decent living by advising or consulting companies in this area of expertise. But when time goes by so are the developments and in the technology world this goes fast, very fast. In the last couple of years the data environment has become bigger and bigger. First there was just data in companies, now you have the combine sources of data to get a clear view about. And the sources keep on changing. Big data used to be a word that was undefined and unable to use. And for many it still is, but others use big data to enrich and enable growth for their companies. By just summing this up you see the changes that happened in the last couple of years and you have to keep up to stay relevant. Learn and gain knowledge is the only key to success in the long term. Artificial Intelligence and Machine Learning powered by optimal use of data and data management will take over many tasks but in the end human creativity and the ability to learn will provide success and the power to make the difference.

Data Management is never finished and neither is learning about it

As you have been in the world of data management you should know that data management is never finished and so is the possibility of gaining knowledge. New books about data management are published recently, research firms keep on researching and find new discoveries. And many companies use the evolution of the technology to grow. Also Communities are built around topics on many different platforms. The possibility to learn is everywhere! Use it in your benefit, data management is never finished…

data-management-expertsRick Buijserd is author and owner of the platform Data Management Experts and a young professional with experience in the world of data. He started his career at a well-known software vendor as channel manager where he learned the skills of indirect sales and managing partners. Financial, HR, Logistics, Warehousing and PSA were the main elements of his software sales. Building relationships with experts and other vendors are part of his DNA.

rickAfter a couple of years he decided to make a switch and landed in the world of accountancy firms. In this period he enabled himself to become a trusted advisor of many accountancy firms in The Netherlands. The area of finance, financial reporting, tax, auditing and other accountancy related activities are no secret to him. Together with his clients he developed many solutions to solve their challenges. In this period the love for data management came above. Accountancy firms are the ultimate example of being data driven. It is all they know.

In the most recent period of his career he stepped into the world of multinationals and as off today he is still active in this world advising around data management and selling software solutions to multinationals who have challenges in the area of data management. Also he is an expert in the area of social selling via LinkedIn and this knowledge has been brought into practice via a LinkedIn Group for Dutch Data Management Experts in which he gathers the top data management experts from the largest companies in The Netherlands to discuss all kind of data related topics.

Data Born Companies and the Rest of Us

harriThis post is a new feature here on this blog, being guest blogging by data management professionals from all over the world. First up is Harri Juntunen, Partner at Twinspark Consulting in Finland:

Data and clever use of data in business has had and will have significant impact on value creation in the next decade. That is beyond reasonable doubt. What is less clear is, how this is going to happen? Before we answer the question, I think it is meaningful to make a conceptual distinction between data born companies and the rest of us.

Data born born companies are companies that were conceived from data. Their business models are based  on monetising clever use of data. They have organised everything from their customer service to operations to be capable of maximally harness data. Data and capabilities to use data to create value is their core competency. These companies are the giants of data business: Google, Facebook, Amazon, Über, AirBnB. The standard small talk topics in data professionals’ discussions.

However, most of the companies are not data born. Most of the companies were originally established to serve a different purpose. They were founded to serve some physical needs and actually maintaining them physically, be it food, spare parts or factories. Obviously, all of these companies in  e.g. manufacturing and maintenance of physical things need data to operate. Yet, these companies are not organised around the principles of data born companies and capabilities to harness data as the driving force of their businesses.

We hear a lot of stories and successful examples about how data born companies apply augmented intelligence and other latest technology achievements. Surely, technologies build around of data are important. The key question to me is: what, in practice, is our capability to harness all of these opportunities in companies that are not data born?

In my daily practice I see excels floating around and between companies. A lot of manual work caused by unstandardised data, poor governance and bad data quality. Manual data work simply prevents companies to harness the capabilities created by data born companies. Yet, most of the companies follow the data born track without sufficient reflection. They adopt the latest technologies used by the data born companies. They rephrase same slogans: automation, advanced analytics, cognitive computing etc. And yet, they are not addressing the fundamental and mundane issues in their own capabilities to be able to make business and create value with data. Humans are doing machine’s job.

Why? Many things relate to this, but data quality and standardization are still pressing problems in every day practice in many companies. Let alone between companies. We can change this. The rest of us can reborn from data just by taking a good look of our mundane data practices instead of aspiring to go for the next big thing.

P.S. The Google Brain team had reddit a while ago and they were asked “what do you think is underrated?

The answer:

“Focus on getting high-quality data. “Quality” can translate to many things, e.g. thoughtfully chosen variables or reducing noise in measurements. Simple algorithms using higher-quality data will generally outperform the latest and greatest algorithms using lower-quality data.”

https://www.reddit.com/r/MachineLearning/comments/4w6tsv/ama_we_are_the_google_brain_team_wed_love_to/

About Harri Juntunen:

Harri is seasoned data provocateur and ardent advocate of getting the basics right. Harri says: People and data first, technology will follow.

You can contact Harri here:

+358 50 306 9296

harri.juntunen@twinspark.fi

www.twinspark.fi

 

Royal Data Quality

The intersection of royalty and data quality was touched on this blog in the post Royal Exceptions 5 years ago, when the Queen of Denmark turned 70 years old. Now when her Majesty just rounded the 75-year mark, it is time to revisit the subject.

Royal Coat of Arms of DenmarkAs always when a Royal event is around the debate on the reason of being for a Royal House stirs up. Putting the historical and emotional arguments aside, let us have a look on the economic arguments.

In Denmark there are two main arguments in favor of having a Royal House:

  • Having a president instead of a Royal House will cost the same anyway
  • The costs of the Royal House is less than the wins from brand value when exporting goods and services

Cost of having a president versus a Royal House

The idea of an expensive presidency is probably founded in looking at the amount of money countries like the United States and France puts into the safety and glory of their presidency.

On the other hand, countries may make their own choice on the level of costs for a presidency. If you look at countries like Ireland and Finland, countries of similar size of population as Denmark, their costs for the presidency is only a fraction of the costs of the Danish Royal House.

Brand Value of the Royal House

Even high-ranking executives in large Danish companies often make the argument of a high brand value attached to the Royal House. However, I doubt they have checked with their own business intelligence department.

In fact, there have not been made a single public available study on the matter, and I doubt any business college researcher will risk the career on doing so.

There was a comic situation some years ago when it was taunted that there was a correlation between Denmark getting a crown princess from Australia and a sharp rise in the Danish export to Australia. The Mary-effect it was called. Sadly, for royalists at least, a sense check revealed that Norway and Sweden had the same development without importing a crown princess from Australia.

Conclusion

I hope the above examples are Royal Exceptions and most other decisions around are taken based on carefully considered facts.

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The Shortcut to Lapland

11th of November and it’s time for the first x-mas post on this blog this year. My London gym is to blame for this early start.

Santa’s residence is disputed. As told in the post Multi-Domain MDM, Santa Style one option is Lapland.

Yesterday this yuletide challenge was included in an eMail in my inbox:

Lapland

Nice. Lapland is in Northern Scandinavia. Scandinavia belongs to that half of the world where comma is used as decimal mark as shown in the post Your Point, My Comma.

So while the UK born gym members will be near fainting doing several thousands of kilometers, I will claim the prize after easy 3 kilometers and 546 meters on the cross trainer.

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Data Quality in Different Languages

The term ”data quality” exists in many different languages.

As reported in the post Häagen-Dazs Datakvalitet, the Scandinavian word for data quality is datakvalitet. Well, actually there is no such language as Scandinavian, but datakvalitet is used in Danish, Swedish and Norwegian all together. Maybe even in both Norwegian languages, though Google Translate only know of one Norwegian language.

In other Germanic languages the words for data quality are close to datakvalitet. In German: Datenqualität. In Dutch: Datakwaliteit.

The above terms are compound words. Even though English is also classified as a Germanic language we see a Latin influence as “data quality” is two words in English. And that goes for all English variants. It is only when it comes to if we have to standardise this or standardize that we are in trouble. British English is best when we have to select if data quality improvement is a program or a programme.

In true Latin languages we have three words. French: Qualité des données. Spanish: Calidad de datos.

And then there are of course terms in other alphabets than latin and other script systems:

data quality in different languages

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The Dangers of being a Global Shopper

The global shopper is a multi-channel beast.

A global shopper may be a tourist or a business traveler buying goods in exciting cities around the world in shops most probable operated by the very same brands that occupies his local high street. The global shopper may also do his business from his living room by shopping online on sites with strange foreign privacy rules and unusual registration forms.

Oxford_StreetBeing a global shopper is risky business.

For example it’s unbelievable why Oxford Street in London hasn’t been made into a pedestrian street long time ago like any other respectable high street in major cities. But no, global shoppers on Oxford Street are constantly in danger of being hit by a red double-decker bus when crossing the street for a good bargain while looking to the right wrong side.

And how about shoe sizes? Measuring systems and standards around the world is a jungle and as a global shopper you will in 8 ½ out of 10 trials pick the wrong number 42.

Going online isn’t any better.

When registering your home address on a foreign site you are on very slippery ground.

If the site is from the United States, and you are not, you have to choose living in one of 50 different states meaning nothing to you. But there is no way around. My favorite state then is Alaska usually being on the top of the list.

Having a postal code with letters in it can be a no go. Not having a postal code is much like not existing at all.

But don’t give up. As a global shopper you will be able to find sites online with absolutely no clue about what an address looks like. Only thing of course will be the question about if you actually will get your goods or have to settle with the credit card withdrawal only.

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