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At this festive time of year, I’ve been scouring online for relevant seasonal wishes. Here is one such wish by Santa Claus, that also suits a few Customer Insight Leaders that I know.
Reading several blogs, I was delighted to find that such a seasonal take on the need for data analytics was published by my friends at Mango software.
Experts and local advocates in the use of R programming language for data science, it was no surprise to see Mango covering this topic.
But, I am indebted to Hannah Evans from Mango for publishing an introduction to the business relevance of analytics, with such a Christmassy twist.
Over to Hannah for a usefully simple example of how analytics can help, to help you feel that bit more festive…
“All I want for Christmas is you big data analytics!”
All businesses have data. But whether it is used to drive business value is another question entirely. Traditionally, technical analysts have made decisions about data technology, without truly understanding the business challenges beforehand, meaning that ‘use cases’ are retrospectively fitted in order to demonstrate return on investment. Increasingly, there is a requirement for organisations to align both business and technical stakeholders, to ensure the business challenges are translated into the right technical solution from the outset.
To demonstrate this, let’s use the example of Mr Claus in the North Pole. Mr Claus is the largest toy manufacturer and distributer in the world, ‘Christmas Inc’. Each year Mr Claus has to deliver gifts to 700 million children worldwide in one night; a task that does not come without its challenges. To make his life (and his elves’) lives easier, Mr Claus would like to start analysing datasets collected from the grotto, to optimise his ecosystem. Rather than investing in a large-scale technology platform, like Hadoop, Mr Claus wants to ensure the ‘data insight’ he gets, answers all his business challenges. Those business challenges will ultimately dictate the technologies the technical elves set up in the workshop.
Mr Claus’ business challenges
So what are Mr Claus’ business challenges? They range from HR to supply chain logistics, to customer profiling and demand forecasting. By asking questions in the right way, the technical elves will be able to translate the business question into an appropriate technical solution and subsequently define the relevant business processes. Mr Claus draws upon a data scientist, from Mango, to facilitate this discussion between business and technical elves.
1. What are the current stock levels of each manufactured toy that I make?
2. What are my elf productivity levels today?
3. How many days are there until Christmas?
4. How many children have sent me letters this year?
5. How many requests for each toy have I had to date?
Descriptive Analytics
The above are examples of business challenges that require a descriptive analytics approach – they aim to answer questions which describe ‘moments’ in historical datasets, e.g. total number, average value or spread of data. This information can simply be presented using a combination of Excel spreadsheets and graphical dashboards.
Mr Claus also wants to know the reasons why certain historical events happened. For example:
1. Why has there been a surge in requests for star wars toys this year?
2. What has caused elf productivity to drop by 25% this year compared to last year?
3. Why did it take me 50% longer to deliver presents in 2014 than it did in 2013?
Diagnostic Analytics
Those are example of diagnostic analytic use cases. They look to answer the question ‘why did something happen?’ so steps can be taken to improve or avoid a situation in the future. These types of analytics are usually presented in a graphical dashboard format.
But Mr Claus doesn’t only want to make conclusions in hindsight about historical data – he wants to be able to analyse trends in historical data to predict certain things about the future; foresight which will allow a more personalised experience for children but also allow Christmas Inc to remain competitive against other large toymakers. For example, Mr Claus wants to solve the following challenges:
1. What gifts are children likely to put on their Christmas lists if they also write down chocolate?
2. What factors determine whether someone gets put on the naughty list?
3. What influences an elf to work longer hours than usual?
4. Which route around the world am I least likely to come across storms?
5. Is there a link between toy trends and geographic location?
Prescriptive Analytics
The above type of questions require a predictive analytics approach. Technical analysts are required to fit models to datasets to identify “rules of thumb” or relationships between different variables. Once a model has been identified, different variables can be tested against the model to determine the influence of variables on that particular model in question. The result of such analytics is usually a forecast report.
Mr Claus also wants to know what he should be doing to optimise production from start to finish, given existing production constraints.
1. Given I only have 24 hours to deliver all my gifts, what is the optimum route to take around the world?
2. What is the most efficient way of producing gifts, ensuring seamless collaboration across the grotto ecosystem, given the machinery I have?
3. How can I minimise the production of waste in the workshop, given the existing processes?
Prescriptive Analytics
What addresses that final list of 3? Prescriptive analytics are required when the business wants to find the best combination of input that either maximises or minimises the output, given constraints. The output of such analytics is usually a report listing recommendations for next steps and are usually the most valuable kind of analysis.
By harnessing data analytics in the ways illustrated above, you can drive huge value in organisation. By reducing complex data sets to actionable intelligence you can ensure more accurate and relevant business decisions are made. Data Scientists at Mango can help you do this.
Specialising in data analytics using the R programming language , Mango draws upon a wealth of industry expertise and diverse team skill-sets to offer bespoke data solutions to global business communities. We help meet requirements at each stage of the data optimisation journey – from use case definition, to infrastructure development to advanced analytics. We aim to be flexible in our approach to delivery, offering services remotely or on-site, long or short-term with big or small datasets to meet our customer’s needs. Our goal is to understand our customer’s business challenges quickly to give them the capabilities to consume data faster, using cutting-edge technologies to drive business efficiencies and ultimately ensure they remain competitive.