Be a Data-Driven Organisation Now!

The latter would mean a root and branch review of how information is consumed across the board. This exercise shouldn’t take more than a month and as a rule of thumb, strategic re¬porting shouldn’t be more than five reports. Also, consider other methods of displaying data, there are plenty off-the-shelf plug and play products out there.

Malaysia is at the cusp of embracing the data-driven business transformation and the model of public private partnerships offers an interesting solution to this. Aimed at boosting big data analytics adoption by businesses, initiatives such as ADAX look at developing an analytics maturity model to assess an organisations’ data driven readiness. This maturity model is focused on improving the consumer experience and takes into account several factors such as organisational culture, people, and technical capabilities. The initiative will eventually see infrastructures such as big data lab, training centres and other facilities being built. The end goal would be to ease organisations to adopt big data analytics into their businesses.

Challenges

Cultural change will probably be the biggest challenge. Analytics shouldn’t be only accessible to the few and neither should it be only for large business initiatives. It is important to integrate analytics into the daily business cadence. Start from the applying analytics to basic reports (scenario building) moving to more complex propensity models. You know you’ve matured when analytics contributes to the overall business planning and strategic development process.

When it comes to analytics, people break away from the traditional data scientists plotting world domination in the corner of the office to a team of people with a broad range of skills that move to the tempo of business strategy and operations. Successful analytics teams are business objective aligned and are a mix of capabilities and skills. These teams are typically consisting of four characteristic; the data junkie, the story teller, the data scientist, and the commercial minded.

Lastly, do not ignore data governance. Organisations that haven’t grasped the importance of understanding data lineage often get caught in discussions relating to “which data is right” as opposed to what is the best use of our data. Appoint a data steward that maintains data integrity, validity, and quality including ownership of the end-to-end data process.