The Journey to Data Analytic
By :Maria Tjahjadi, VP of Data at tiket.com,
as published at CIO Advisor APAC Magazine (https://www.cioadvisorapac.com/magazines/March2019/Data_Analytics/, page 19–20) and presented at Big Data & AI Leader Summit, Jakarta
What is data driven organisation and why should we care about it?
Data maturity stages based on Dell is about how ready an organisation to utilise a data. Every organisation should go through these stages to achieve data driven organisation.
If we realise that our organisation has multiple reporting systems with each division generating ad-hoc reports, the lack of data integration due to scattered data sources causes questionable accuracy and reliability in their own reports. This is identifiable that the organisation is in data awareness phase. Focus on building these capabilities, database modelling, data standardisation, and a reporting system is top priority to enable the next phase.
Data proficiency is the stage when we already have a company wide reporting system in place but data quality become the next question. The source consists not only structured data, but also unstructured one. The focus in this phase is to integrate more data sources into the new data platform and to implement data management strategy to address the data quality issue.
Data savvy phase is ensuring advance analytic is in place. Not only optimising the existing data platform, but the organisation also focuses on implementing advance analytic, such as prediction model. Two important elements in this phase are choosing the right analytic platform and choosing the right people. To make sure you are in the right path, every analytic that is done should be able to answer or support business questions.
“What is Data Driven exactly?”
In data driven phase is simply — no data no decision. All data that has been integrated in one single analytic platform, where each division is ready to perform “self service” analytic as well. The focus in this phase are embedding advance analytic seamlessly to the business process, scaling beyond a standard analytic platform and moving out from predictive to prescriptive analytic.
Based on study by McKinsey Global Institute, in data driven phase, data and analytic are the main factors for changing the nature of competition. Not only supporting massive data integration and real time analytic, but also radical personalisation, driving the innovation and enhancing decision making.
Organisation that are planning to start the journey towards analytic, data maturity assessment is the starting point. The assessment should be done not only for the technology, but also for people and process. Based on the study that has been done by MIT Sloan Management Review, the biggest obstacle is not the data, but those who lack of understanding of how to use analytic to improve the business and lack of management bandwidth.
At tiket.com, we start off from data maturity assessment to see the current stage and what kind of technology, team, and process that should to be established.
Building the team was one of the main priority after the first assessment. By looking to the organisation’s business model and the existing team capabilities, adopting centralised organisation model has been a good choice. Implementing centralised organisation model refers to analytic capabilities that resided in one team to server, various business units with diverse projects. This structures makes it easier to work in various projects with strategic priority and it can drive a centralised analytic direction for the whole organisation.
In parallel with team building, technology platform was being chosen by evaluating options in the market, either for the analytic platform or visualisation. Some criteria for the selection are able to process massive structure or unstructured data with minimum maintenance and a simple and user friendly visualisation tool. The idea to produce result as quickly as possible to integrate the data and show the result to the business users.
By implementing those strategies with the right team and technologies, within four months the team was able to develop data platform that integrates and standardises the data to serve various business units. Not only that, we also solve several low hanging fruit challenges with advance analytic. It is a very important thing to remember, you should start to solve important challenges that can demonstrate value of the data and analytics.
“Okay. What’s next?”
Up to this moment, we are still continuously refining platform, team, and process for improvement and will never stop as long as the business still runs. Any projects that we do always start with business questions, understanding the challenges or the goals before working on the data that will yield the insights.
Not only solely depending on development and analysis, it is important for the team members to become agent of change to achieve data driven organisation and the data culture, where it should start from the analytic team itself.
Last but not the least is executive support. Without this element, it will be difficult for any organisation to become data driven. By supporting the data and analytic initiatives, executives can see how data can be part of product or service that we sell and it can be a fast track for innovation cycles. With these two important elements present, it can be a differentiator from the competitors.
