Author: Santiago Tacoronte

The D in GIDAR Analytics: Data

by Santiago Tacorontein Uncategorized

After defining clear Goals and collecting as much information as possible (clarifying key questions), you will have a good idea of the data that you need.
Here you want to be methodical. That is the technical part that requires extracting data, access to data sets, databases, build data models and data cleansing. That means that even if you or your team are not in charge of this part, you need to prepare a full brief.

What data do you need?

In the previous step, information, you should have collected the key questions to answer. They are the starting point for the data collection.

You need to write down the questions if you haven’t already and figure out which data you need to answer them.

Don’t be shy, take this initial list as a wish list, so put everything you think could help answer your key questions. 

How to collect and store the data 

In a spreadsheet, list all the questions, data sources and fields, you need to answer the key questions you gathered. 

The next step is the data gap analysis. For this section, we can use any validated gap analysis technique. If you want to keep it simple, you can start with, availability, accessibility and DQI (Data quality Index).

  • Availability refers to the mere existence of the data; do we have competitors data? It is usually a binary result, either yes or no.
  • Accessibility is a step after confirming availability, and it answers the question, can we access the data? Here you might get yes, no or yes but. For example, yes, but we cannot use specific fields due to privacy.
  • DQI or Data Quality Index. That is a quality of measure for the data we will use, and it answers the question. Can we rely on this data? DQI can become complicated, but I recommend you to make sure that the information is accurate, complete and unique if you want to know what these mean have a look into the Introduction to Business Analytics course. And if you don’t have much time, look at the data quality charts presented here.

Examples of Data points

  • Examples of Data  for “Jumpy Shoes”:
  • Total sales of “Jumpy Shoes” by hour of the day, day, week, month, quarter of year.
  • Total sales of “Jumpy Shoes” by model
  • Total share of “Jumpy Shoes” sales by model.
  • Customer that bought “Jumpy Shoes”
  • Demographics
  • Psycographics
  • Price history of “Jumpy Shoes”

In a more DATA friendly format:

ModelDateTimePriceSizeChannel  Oder IDCustomer ID
Shoe Gx20/03/20201:23pm76.538Web1214914Customer1
Shoe Gy24/03/20209:34m4942In Store85895798Customer2
Example of a table with sales data
Customer IDAgeGenderPost CodeNumber of PurchasesLast PurchaseCustomer Lifecycle Value
Customer124Female4057319/01/2020146.74
Customer244Male4914120/05/201956
Example of a table with Customer data

Final Remark

By the end of this step, you should have collected and prepared the data you will use for the analysis.

The I in GIDAR Analytics: (Business) Information

by Santiago Tacorontein Business Information2 Comments on The I in GIDAR Analytics: (Business) Information

Information or better said Busines Information is an essential step in the GIDAR Analtyics framework that is sadly commonly ignored by Analytics teams. 

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The problem when you don’t use Business Information

When you get a Business Analytics request, the usual course of action for Data/Analytics/Insights teams is to jump into finding answers immediately. You send analysts and engineers to collect and analyze data when there is already much-uncovered wisdom.

Being Busy is not always being successful

What happens when you do that is that you neglect a ton of beneficial knowledge that will help you complete the project in less time and with more chances of succeeding.

What is Information in the context of GIDAR?

In this case, business information refers to context, known facts, know-how and experience from stakeholders, and subject matter experts. In one word, WISDOM. There is much wisdom in any company that for one reason or the other (called Knowledge Management in modern business) not always is surfaced. 

How to acquire Business Information?

Obtaining Business Information is mostly asking, asking and asking. You need to wear your Sherlock Holmes detective hat and interrogate key business people to extract critical knowledge. 

Find the Wisdom around you. It will save you plenty of time and you will be set for success.

This phase’s outcome: you want to have information that helps us frame the right questions for the analysis step.

For example, if the objective is to increase sales (refer to Goals to find a detailed one), you shall approach the sales managers or the experienced salesforce. Then you will and ask them about their ideas on increasing sales or things like our audience.

This step’s objective is to find the existing information and knowledge before anything else. 

Business Information Sample Questions

Some common Business Information questions people make:

  • What do you know about the Goal?
  • What is the business model?
  • What is marketing doing?
  • What are the usual complaints of the customers?
  • Has it been done before? How did you do it last time?
  • How will you do it?
  • Where can I likely fail? 
  • Who knows a lot about this topic?
  • Who is responsible for the actions?
  • Is there any restriction or limitation?

Hint: Make sure you give credit to all your sources of information.

Why is Information sometimes more critical than Data?

I assure you that there are people that know a lot more than you in your company. Ask them! Don’t run the project in isolation. They will love to help. They will gift you with hypothesis and ideas to complement your analysis and things that you can straight include in the actions section. You don’t need to do Analytics to make common sense.

Outcome: Key Questions

By the end of this step, you will have a list of critical questions to answer with data in your analysis:

  • Why “Jumpy Shoes” sales always spike in March?
  • Where are our customers dropping?
  • Who are the competitors of “Jumpy Shoes”?
  • How does the price of “Jumpy Shoes” impact their sales? 
  • What can we and what can’t we do?
Screenshot of the GIDAR anlytics canvas with Key questions around business information

Do not confuse the critical questions with the Goal. The goal remains the same, but the Key Questions are a great vehicle to produce a robust analysis and actions.

The G in GIDAR Analytics: Business Goals

by Santiago Tacorontein Business Goals, Uncategorized2 Comments on The G in GIDAR Analytics: Business Goals

The G in GIDAR: BUSINESS GOALS

Goals are intrinsic to any business, even if we do not explicitly declare them, there are always goals behind any activity. A known problem in Business is, however, the inability to articulate Business Goals properly.

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Business Goals are the first and essential step in the entire GIDAR framework. Without purpose, there is no project. If after your stakeholder’s meeting or Business Goals Workshop you don’t have a clear understanding of what you are trying to achieve, you shouldn’t probably be spending resources. In that case, it would help if you revisited your company vision, mission and strategy.

The best way to set a successful Goal is to use SMART goals.

Business Goals must be:

● Specific: If possible numeric

● Measurable: You should be able to track it

● Achievable: Must be something doable (Avoid x10’s)

● Relevant: Have to bring a positive impact.

● Time-bound: Must have a beginning and an end in time.

One more thing your goal should contain is as much as possible a baseline. If you are to increase sales, you should know where your sales were last year or last month.

The more thoroughly you define these steps, the more likely you are to succeed.

Examples of poorly defined Analytics Goal:

● Increase customer NPS (Net promoter Score)

Example of well defined Analytics Goal:

● Increase average customer NPS from 4 to 25 – Specific

● We will use the customer surveys to obtain the data and process it into a monthly report. – Measurable

● We are confident to reach 25 because that is the industry average. – Attainable

● Customers with NPS above 20 spend, on average $100 more per year. – Relevant

● The analytics part of this project will be completed between 20 and 25 days. After delivering Insights and recommendation, we expect four months to implement actions and another 60 days before we measure the results. – Time-bound

Examples of poorly defined Analytics Goal:

● Increase sales

Example of well defined Analytics Goal:

●Increase sales for “Jumpy Shoes” Category by 5% from 10,000 units/month to 10.500 Units month. – Specific and with a baseline

● We will use the ERP data to measure the increment and Marketing Data to assess the campaigns’ impact- Measurable.

● The 5% is based on the industry forecast for these products next year and the competitive market share.- Attainable

● “Jumpy Shoes” category A represents 20% of our global sales. Moreover, a 5% increase will enable the launch of a new shoe category – Relevant.

● We will measure results on a bi-weekly basis during the next six months. There is the first milestone of +2.5% on month three and a final report after month 6.

Note how we have gone from a broad question to a more specific query. When you have worked out such detailed Business Goals, it is more evident for all parties what they are trying to achieve. 

Business Sponsor and Analytics teams can now move to the next phase of GIDAR, Information.