Why Master Data Management is Not Just a Nice-to-have…

Sometimes the ideas for a blog just land on your desk without any effort. This time, all the effort was made by one of the world’s largest fast moving consumer goods companies with 355.000 employees worldwide.

But this is not a guarantee for smart process and data management as the next experience from yours truly will illustrate.

The Anamnesis

One rainy day, the tenth of May, I receive a mail piece with a nice promotional offer: buy a coffee machine for one euro while you order your exquisite cups online. On rainy days you take more time to read junk mail and sometimes you even respond to them. So I surfed to their website and filled out the order form. After introducing the invoice data (VAT number,invoice address,…) an interesting question popped up:

Is your delivery address different from your invoice address?

As a matter of fact it was, it was the holiday season and the office was closed for a week but I was at a customer’s site and thought it would be a good idea to have it delivered there.

So I ticked the box and filled in the delivery address.  That’s when the horror started.

Because, when I hit the order button, there was no feedback after saving, no chance to check the order and wham, there came the order confirmation by e-mail.

Oops: the delivery address and the invoice address were switched. Was this my fault or a glitch in the web form? Who cares, best practice in e-commerce is to leave the option for changing the order on details and even cancelling the order, right? Wrong. There was no way of changing the order, all I could do was call the free customer service number to hopefully make the switch undone.

10th May, Call to Consumer Service Desk #1 

IVR: “Choose 2 if this is your first order”

Me: “2”

Client service agent: “What is your member number?

Me: “I don’t have member number since this is my first order. It’s about order nr NAW19092… “

Client service agent: “hmmm we can’t use the order number to find your data. What is your postcode and house number?”

Me: “This is tricky since I want to switch delivery address with the invoice address. You know what, I’ll give you both”.

Client service agent: Can’t find your order”

So, I am completely out of the picture: not via the company, the address, the order number, let alone a unique identifier like the VAT number

Client service agent: “Please send a mail to our service e-mail address “yyy@zzz.com”.

Me: “Send e-mail” Result: no receipt confirmation, no answer from this e-mail address. Great customer experience guys!

10th May Call to Consumer Service Desk #2

Client service agent: “Oh Sir, you are calling the consumer line, you should dial YYY/YYYYYY for the business customers”

Me:" But that’s the only phone number on your website and the order confirmation???!!!"

10^th May 2 PM Call to Business customer service #3

Client service agent: “Let me check if I can find your order”… (2’ wait time) “Yes, it’s here how can I help you?”

Me: “I want to switch the invoice with the delivery address”

Client service agent“OK Sir, done”

11^th May: The delivery service provider sends a message the delivery is due on the original address from the order.

No switch had been made…

Call to DPD? Too late.. these guys were too efficient...

The Diagnosis, What Else?

Marketing didn’t have a clue about the order flow and launched a promotion without an end-to-end view on the process which resulted in a half-baked online order process: no reviewing of the order possible, no feedback and the wrong customer service number on the order confirmation.

Data elements describing CUSTOMER, ORDER and PRODUCT may or may not be conformed (from the outside hard to validate) but they are certainly locked in functional silos: consumers and companies.

Customer service has no direct connection to the delivery process

The shipping company (DPD) provided the best possible service under the circumstances.

And this is only a major global player!  Can you imagine how lesser Gods screw up their online experience?

Yes, it can get worse!

One of my clients called me in on a project that was under way and was seriously going south.

What happened?  The organisation had developed a back office application to support  a public agenda of events. As a customer of this organisation you could contact the front desk who would then log some data in the back office application and wrap up the rest of the process via e-mail. Each co-worker would use his own “data standards” in Outlook so every event had to be handled by the initial co-worker if the organisation wanted to avoid mistakes. No wonder some event logging processes sometimes took quite a while when the initiator was on a holiday or on sick leave…

A few months later -keep that in mind- the organisation decided to push the front desk work to the web and guess what? Half the process flow and half the data couldn’t be supported by the back office application because the business logic applied by the front desk worker wasn’t analysed when developing the back office app.

Siloed application development can lead you to funny (but unworkable) products

So, please all you folks out there, invest some money in an end-to-end analysis of the process and the master data. It’s a fraction of the building cost and it will save you tons of money and bad will with customers, coworkers and suppliers.

Afterthoughts on Data Governance for BI

Why Business Intelligence needs a specific approach to data governance

During my talk at the Data Governance Conference, at least one of my audience was paying attention and asked me a pertinent question. “Why should you need a separate approach for data governance in Business Intelligence?”

My first reaction was “’Oops, I’ve skipped a few stadia in my introduction…” So here’s an opportunity to set things right.

Some theory, from the presentation

At  the conference, I took some time to explain the matrix below.

Data portfolio management as presented at the 2016 data governance conference in London

If you analyse the nature of the data present in any organisation, you can discern four major types.

Let’s take a walk through the matrix in the form of an ice cream producer.

Strategic Data: this is critical to future strategy development; both forming and executing strategy are supported by the data. By definition almost, strategic data are not in your process data or at best are integrated data objects from process data and/or external data. A simple example: (internal) ice cream consumption per vending machine matched with (external) weather data and an (external) count of competing vending machines and other competing outlets create a market penetration index which in its turn has a predictive value for future trends.

Turnaround Data: critical to future business success as today’s operations are not supported, new operations will be needed to execute. E.g.: new isolation methods and materials make ice cream fit for e-commerce. The company needs to assess the potential of this new channel as well as the potential cannibalizing effect of the substitute product. In case the company decides not to compete in this segment, what are the countermeasures to ward off the competition? Market research will produce the qualitative and quantitative data that need to be mapped on the existing customer base and the present outlets.

Factory Data: this is critical to existing business operations. Think of the classical reports, dashboards and scorecards. For example: sales per outlet type in value and volume, inventory turnover… all sorts of KPIs marketing, operations and finance want every week on their desk.

Support Data: these data are valuable but not critical to success. For instance reference data for vending locations, ice cream types and packaging types for logistics and any other attribute that may cause a nuisance if it’s not well managed.

If you look at the process data as the object of study in data governance, they fall entirely in the last two quadrants.

They contribute to decision making in operational, tactical and strategic areas but they do not deliver the complete picture as the examples clearly illustrate. There are a few other reasons why data governance in BI needs special attention, If you need to discuss this further, drop me a line via the Lingua Franca contact form.

Data Governance in Business Intelligence, a Sense of Urgency is Needed

The Wikipedia article on data governance gives a good definition and an overview of the related topics. But although you may find a few hints on how data governance impacts the business intelligence and analytics practice, the article is living proof that the link data governance with BI and Analytics is not really on the agenda of many organisations.

Sure, DAMA and the likes are reserving space in their Body of Knowledge for governance but it remains on the operational level and data  governance for analytics is considered a derived result from data governance for on line transaction processing (OLTP). I submit to you that it should be the other way around. Data governance should start from a clear vision on what data with which degree of consistency, accuracy and general quality measures to support the quality of the decision making process is needed. In a second iteration this vision should be translated into a governance process on the source data in the OLTP systems. Once this vision is in place, the lineage from source to target becomes transparent, trustworthy and managed for changes. Now the derived result is compliance with data protection, data security and auditability to comply with legislation like Sarbanes Oxley or the imminent EU directives on data privacy.

Two observations to make my point

Depending on the source, between 30 and 80 percent of all Business Intelligence projects fail. The reasons for this failure are manifold: setting expectations too high may be a cause but the root cause that emerges after thorough research is a distrust in the data itself or in the way data are presented in context and defined in their usability for the decision maker. Take the simple example of the object “Customer”. If marketing and finance do not use the same perspective on this object, conflicts are not far away. If finance considers anyone who has received an invoice in the past ten years as a customer, marketing may have an issue with that if 90 % of all customers renew their subscription or reorder books within 18 months.  Only clear data governance rules supported by a data architecture that facilitates both views on the object “Customer” will avoid conflicts.

Another approach: only 15 – 25 % of decision making is based on BI deliverables. On the plus side it may mean that 75 % of decision making is focused on managing uncertainty or nonsystematic risk which can be fine. But often it is rather the opposite: the organisation lacks scenario based decision making to deal with uncertainty and uses “gut feeling” and “experience” to take decisions that could have been fact based, if the facts were made available in a trusted setting.

Let’s spread the awareness for data governance in BI

More on this in my speech at the Data Governance Conference in London, the 17thMay

In the meantime,I’d like your opinion on this matter. It takes just three minutes to answer four questions. 

Many thanks in advance!

May I have three minutes of your time?

But I need your help...

To asses the present state of art in Data Governance and Analytics: how are data definitions, formats, locations, security, privacy and other aspects governed for analytical purpose? But most of all, why are you governing data and what is the level of data governance in your organisation?

Get Lingua Franca’s Presentation on the Data Governance Conference Europe 2016

“How Data Governance Works with BI”

But before we send you the proceeds of the conference, we ask you for a favour in return.

Fill in four answers on a questionnaire you can find here. We expect about 400 answers from all industries in the EU and the Americas. A high level report will be integrated in our presentation but you will get the full report if you tick the box on the form. And rest assured, you will not be spammed with offers or other unwanted solicitations!

For a full programme on the Data Governance Conference, follow this link.

Many thanks in advance!

Bert

A Little Side Step into Norway: BI 2016 Forecast

The Norwegian leading blog on Business Intelligence published my view on BI in 2016.

Check the prognosis here and get back to me at the end of the year to see if my crystal ball was clear on at least a few issues.

A Little Late: My Professional New Year's Resolution

Book Review: Business Analysis

3rd Edition, edited by Debra Paul, James Cadle and Donald Yeates

Preamble: the island and the continental species

When BCS, the Chartered Institute for IT deems a book worth publishing, it is certainly worth reviewing from a continental point of view. Why? Because experience shows that the UK’s  business analyst has not exactly  the same profile as the variety on the mainland.

On the British Isles, a business analyst covers a much wider scope: “One of the most important aspects of a business analysis project is to decide what the focus is and which areas need to be investigated. For example, on some projects the focus may be to explore possible improvements on how part of the organization works. In this case, we might begin by examining all of the current working practices, including the staffing and job roles, and the work may focus on analysing and evaluating the options for the future business system. Another project may focus on the IT system needs and whilst understanding the situation and all of the stakeholder perspectives is important, the potential for the use of IT to improve the business system will dominate the analysis.” (p .59)

Clearly, the island species covers a far broader scope than the continental one. Of the hundreds of business analysts I have met on projects, in training courses and seminars, ninety percent come from an IT background. In the application or OLTP world, I have met with dozens of ex-developers who became functional analysts and expanded their horizon towards business analysis. In the OLAP or analytics world, there is dominant share of DBAs who became business analysts. Suddenly I realise that I am more of an island species as I evolved from sales, marketing and finance into business analysis and studied computer science to make sure I can communicate with the designers and developers.

A comprehensive introduction

The editors take you on a journey through the analysis practice, defining the concept, the competencies and introducing strategy analysis, business analysis as a process, touching the investigation techniques and introducing stakeholder analysis. After modelling the business process, defining the solution and making the business and financial case, the requirements are discussed as well as a brief introduction to modelling the requirements and delivering the requirements and the business solution.

Delivering this body of knowledge in fourteen chapters on 280 pages indicates this book is a foundation for practitioners.

Models, models and… models

The 280 page book is packed with models, 112 of them are illustrated and explained as well as integrated in a logical process flow of the business analysis practice.

In that sense, the foreword of president of the IIBA UK Chapter, Adrian Reed, hits the spot when he calls it “an extremely useful resource that will referenced by new and experienced practitioners alike”.

Novice analysts can use this book as an introduction to the business analysis practice in the broadest sense while experienced business analysts will consider it a valuable placeholder for useful frameworks, concepts and material for further study. The Reference and Further Reading sections at the end of each chapter contain extremely useful material.  With regards to “further reading”  there is a caveat I need to share with you. It‘s not about the book itself but more about models in general.

A caveat about models

Let me tell you a little story from my marketing practice to illustrate my point.

A very familiar model in portfolio management is the Boston Consultancy Group’s  Share Matrix. It is used on a strategic level to analyse business units and in the marketing practice, the product portfolio is often represented and analysed via this model.

For those not familiar with the model, here’s a little reference to the theory: https://en.wikipedia.org/wiki/Growth%E2%80%93share_matrix

When I worked for a multinational FMCG company I discovered what I called “Cinderella brands”. These were brands with a small market share, low growth and considered a dead end street for the marketer’s career. You could find product managers with little ambition in that position, fixing up and manoeuvring to keep the brand afloat while people higher up in the organization where waiting for the right moment to axe the brand. I managed to convince the people with the axe that an appropriate marketing approach cold not just save the brand but grow it into a profitable niche product, sometimes contributing more than their so-called cash cows. We built the business case on processed cheese with a budget on a shoestring and proved our point that a model can never take over from thorough analysis and critical thinking. After that, nobody mentioned “dogs” anymore, “Cinderella” became the household name for forgotten brands with unrealized potential. (And we got much more business from the multinational.)

The illustration below from an academic author shows exactly what can go wrong when models take over from scrutiny and  critical thinking.

These are the questions to ask when you look at a growth share market:

·          Who says cash cows don’t need substantial investment to maintain their dominant market share and keep up with market growth? Ask Nokia if you doubt it.

·           Who says dogs need to have a negative cash flow? Sure,  if your marketing spend is based on the same mental models as those for stars and cows you will be right but guerrilla marketing techniques may prove the  opposite.

·           Who says stars’ growth will continue for eternity? Ever read “Crossing the Chasm” by Geoffrey Moore? Especially in high tech marketing, novelties may only appeal to the techies but never reach the mainstream market…

In fact, question marks are in the only quadrant in the above model where some form of nuance can be observed…  Notice the expression “analyse … whether…”

In conclusion:  follow the editors’ further reading advice. It will help you to become a mature business analyst providing your customers not only the “know what” and some of the “know how” as described in the book, but also the “know why”. Wisdom may be harder to quantify but its value is beyond doubt in the business analysis practice. By the way, from the same editor, I recommend “Business Analysis Techniques” to increase your know how.

Regular updates needed

The business analysis practice evolves rapidly and the only criticism I can come up with is the lack of an accompanying website with extra updates and reference material. Let me add at least two of them:  a benefit map and the business canvass models are very much in the business analysis practice today.

To conclude, all you continental business analysts out there, buy the book and increase your knowledge by an order of magnitude.

Available at http://shop.bcs.org, paperback ISBN: 978-1-78017-277-4