Digital Data Assets Analytics Influencing Xmas
All enterprises 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 enterprises to ensure the business challenges are translated into the right technical solution from the outset.
To demonstrate this, let’s use the example of Santa in the North Pole. Let’s say Claus industry is the largest toy manufacturer and distributer in the world. Each year Santa has to deliver gifts to Millions of children worldwide in one night; a task that does not come without its challenges. In order for him and his elves to be efficient, Santa would have to analyse data collated to optimise his ecosystem stored in the form of decentralized assets. Making this possible and getting insights and answers to all his business challenges he can use technology platform such as DDAM to accurately fulfill his desired plan. Those business challenges will ultimately dictate the technologies the technical elves set up in the workshop.
Business challenges
Business challenges range from 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 DDAM, 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 2018 than it did in 2017?
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 digital data assets.
We don’t only want to make conclusions in hindsight about historical data — we want 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, Santa 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.
Santa 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?
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. DDAM can help you do this.
Conclusion
In future, data will become the most important production material. Anticipating future issues of data sovereignty, more data will be stored in a decentralized data storage platforms, which can ensure data privacy. Existing data also creates a silo situation among enterprises, where information remains in private. This will be
broken, and blockchain technology will reconstruct the credit society. The decentralized data asset management, which maintains data sovereignty, will become the strategic consensus of the world’s leading enterprises. The popularization of artificial intelligence and machine learning will further amplify enterprises’ hunger for data asset management.
It can be said that in the era of data sovereignty, whoever manages decentralized data assets best will have the key to understanding and manage data in the future. Only through technology management and usage of our own data can we fully protect the privacy of the times, and facilitate collaboration with others in the future effectively.
DDAM aims to become the underlying infrastructure for decentralized data asset
management in the future, helping all data producing managers to realize the value of data assets and creating a real social value with blockchain technology.
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