Business Intelligence, Data Nerds, GDPR

BI – All Feet on the GDPR-Gas Pedal

IMG-20171217-WA0000Business Intelligence and GDPR (General Data Protection Directive) cannot be divorced. They can almost be viewed as rivals in collaboration with each other for mutual existence. In business intelligence, Customer data behavior is the most valued analysis. This because companies have understood that customer is synonymous with business. Most companies with a vision are totally dedicated to customer Service. To serve a customer satisfactorily, a company needs to know and understand its customers.

For example, at the least, a bank wants and needs to know which of its customers saves a lot, spends a lot, buys shares, bonds etc to be able to make offers to specific customers that meet the specific customer’s needs.

Another example is a retailer that needs to know its customer’s preferences to be able to suggest the next buy, a suitable payment method, a pick up place, a delivery time etc.

All this means that data is saved in a vault somewhere and an analyst is looking into this vault every now and then. In mature BI organizations, there are tools for mining and analyzing this data as well as numerous analysts looking for clues in the data.

GDPR demands that we are aware and transparent about:

  • What we are saving about a customer
  • Where we are saving it
  • Who has access to the saved data
  • For what purpose we are saving the data
  • The length of time we are saving
  • The security of the saved data

The deadline is five months away. The reality is no one is done, let alone certain of what is expected of them for compliance. So all the feet that can be spared are on the GDPR-gas pedal. Mine too, though I cannot with all certainty be spared. Which leads to the question: Where did time go?

Tick-TockIs time simply a matter of counted hours that run through the fingers without stopping for a hello and goodbye?

Or is time the space between different things, different activities and different people? The space between eight hours of work, eight hours of sleep and vice versa?

The space when one arrives home, exhausted, ready to make a quick dinner for the household before dropping dead in the sofa or in bed.

The territory between choices. To go to bed or to log into the work computer and work two more hours? That is the question.

Is time the margins surrounding knowledge, perspective, respect, estimation and prioritization? Other aspects of life that create balance?

The space between:

  • The first time time you heard about GDPR and The first thing you learned about GDPR.
  • The first time you spoke about GDPR and the day you started planning for GDPR.
  • GDPR implementation, GDPR compliance and the maintenance of the Policy

Or is time all the virtues and demands warped into each other?

BI for Start Ups, Business Intelligence, Data Nerds

Business Intelligence as a Way of Life

In my opinion, the essence of Business Intelligence (BI) is not the what but the why. You have heard that before, so it will annoy you to hear such a cliché, especially concerning as serious a matter as BI.

Bear with me, please.

Of course, BI is different for different businesses depending on the level of maturity, the market share and the revenue. Mature, well established businesses probably need BI for the complex purpose of keeping the customers they already have and where plausible, for attracting new customers. It is called Improved Sales.

New businesses need BI for the sole purpose of establishing a presence in a new, probably unknown, and probably occupied market. What we now call BI has existed in many formats from as long as time is ancient. Market Research for instance:

  • What do you want to sell? What needs selling?
  • Is there a Buyer? Is there a need? Why do you think there is a need?
  • Does what you want to sell already exist? If yes, how much of it exists? Why do you want to sell it anyway? If no, why isn’t any other clever bugger selling it?
  • Location? Have you found a perfect location? Why is it perfect?
  • How about the competition? What do you plan to do differently? Why do you want to do anything different?

You see the whys? It is a step by step progression from what to why of course, but the most actionable knowledge comes when you have the answer to the question Why.

Here is a breakdown of my theory: Say you ask for a report of the potential customers in the vicinity of your new business venture. Say that after a lot of research and consideration, you decide that your new business venture should be Selling Beautiful Handmade Wallets. You will be designing the best wallets at home and and retailing them in a small Online store in a back alley behind the online garage in the city called Online Nowhere.

  1. Number of potential customers = 1,4 customers
  2. Promising Buyers = Married Women
  3. Expected Revenue = 10,2
  4. Currency = SEK

You even get an example customer:

  1. Customer Number = SE4321 (Swedish Customer)
  2. Customer Name = Lim Pan
  3. Customer Payment method = Credit Card
  4. Customer Address = 43 Trinity Stockholm
  5. Customer Gender = Female
  6. Customer Age = 37.5
  7. Customer First Order = 12th June 2014
  8. Customer Most Recent Order = 12th June 2017
  9. Customer Average Order Amount = 557
  10. Customer Currency = SEK
  11. Customer Marital Status = Married
  12. Customer Family = Two Children

Imagine you get the above simplified report including the detailed information on a specific customer, what catches your attention? Is it the average amount, the date of birth, the gender or the payment method? The more urgent question is, Why do you want to know anything at all about a specific customer? Is it for marketing, is it for Service improvement or is it for analysis of customer behavior?

What is Service improvement for you?

I would like to suggest that the best way to utilize BI in this case is to find out:

  1. Why you entrust your life to a wallet?
  2. Why would anyone want your beautiful wallets?

Don’t get insulted, they are beautiful wallets! But, there are multitudes of ugly wallets that do the job! So, is it that your beautiful wallets function better than the ugly ones? Is it possible that your beautiful wallets are cheaper or pricier than the ugly ones? Why is that good? Is it good for you or for the intended customer?


Data says that the potential customer pays with a credit card. Why Credit Card?

Could the potential customer be persuaded to pay by other means?

Why is the potential wallet buyer a woman? Do women use wallets?

Data says, there are 1,4 potential customers in Nowhere. Why 1,4?

How many people live in Nowhere? Why don’t the space occupants need wallets?

Why the best wallets in the world? Why not cats and dogs? Why not hair pins?

Why retail? Why a small Online store in a back alley behind the online garage in the city called Online Nowhere? Why not a big wholesale beside Best Priced Wallets Online?

If you cannot gather enough data or enough gossip to answer most of these questions, and more, you can kindly be accused of gambling.

With BI, you do not always have to have a huge complex databases, the latest BI tool, or a team of BI experts running around their tails recreating age old KPIs to send out age old reports.

BI is a way of life.

It is the self preserving choice to not jump on any train without asking where it is going.

The cool-headed decision to not spend a dime without checking how many dimes you have left.

The safety precaution of not walking a dark alley alone.

The SMART goal that needs a background, a baseline, an investment, a commitment and a future.

BI Tools, Business Intelligence, Graphic User Interface Design, IT Management

An Introduction to Business Intelligence

Gartner defines Business intelligence (BI) as:

An umbrella term that includes the applications, infrastructure and tools, and best practices that enable access to and analysis of information to improve and optimize decisions and performance.

It is an OK definition. I like OLAP’s definition better:

The term Business Intelligence (BI) refers to technologies, applications and practices for the collection, integration, analysis, and presentation of business information. The purpose of Business Intelligence is to support better business decision making. Essentially, Business Intelligence systems are data-driven Decision Support Systems (DSS).

Finance Online and other more revenue focused organizations go into details and lists about what constitutes Business Intelligence. For example:

  1. Data mining
  2. Online analytical processing
  3. Querying
  4. Reporting

A break down of Business Intelligence (BI) is made at Investopedia:

Business intelligence grew out of the conviction that managers with inaccurate or incomplete information will tend, on average, to make worse decisions than if they had better information. Creators of financial models will recognize this as a “garbage in, garbage out problem.” Business intelligence is meant to solve that problem by bringing in the most current data that is ideally presented in a dashboard of quick metrics designed to support better decisions.

As you can see, Business Intelligence is both simple and complex in all the ways it should be.

I would like to suggest that:

Business intelligence (BI) is growing out of the knowledge that decision makers with selective/subjective, inaccurate, reliable, manipulated or incomplete information tend, on average, to make catastrophic decisions. This, as compared to better decisions made based on accurate, reliable, non-manipulated and complete information from multiple objective sources.

In decision making, as in Business Intelligence, the keywords are “Crap in, Crap out.” Therefore, BI’s main goal should be to reduce the challenges faced in Decision Making by bringing in the most current data – accurate, reliable, non-manipulated and complete – from multiple objective sources.

To make this data available and fathomable for decision makers, it should ideally be visualized in user friendly presentation tools chosen with great consideration for the specific decision maker’s needs and technical maturity.

To explain what I mean, I will give the example of the yearly/quarterly comparison reports for BI tools. Every new report announces the latest “best” tool in different categories.

The only message missing from the comparison report is:cropped-db-image.png

Please note before you purchase this fantastic BI tool: It doesn’t matter how fantastic the GUI (Graphic User Interface) is, in BI & analytics, if the data is crap, the decision maker will not be jubilant about the GUI.

One of the lessons I have learnt working with BI is that, the frustration caused by unreliable data, overrides the pleasure of a beautiful GUI, every single time.