#{LINKS}!
#!LOGIN!#
Research from McKinsey proves that data analytics has the potential to transform how organizations coordinate, operate, manage talent and create value. This article elaborates on how organizations benefit from gaining data analytics maturity.
Gaining analytics maturity
The frustration of spotting an opportunity only to realize it’s too late. Does that sound familiar to your organization? Data mature organizations have the advantage of being able to spot opportunities way in advance, while they’re still invisible to the human eye.
A recent survey by Gartner however showed that as much as 87.5% of respondents had low data and analytics maturity level, meaning they fall into ‘basic’ or ‘opportunistic’ levels of business intelligence capabilities. Those at the basic level find that individual business units pursue their own data and analytics initiatives as stand-alone projects, lacking leadership and central guidance and usually using spreadsheet-based analyses and personal data extracts. This setup constraints analytics leaders who are attempting to modernize business intelligence.
So how do ‘mature’ or successful companies act? According to Urs Hölzle, one of Google’s first employees, enterprise use of data is evolving in ways that should excite both data scientists and the customers they serve. According to Urs, more businesses now analyze data to make important long-term strategic decisions as well as real-time choices. To get an overview of the main developments in the field of successful data strategies, please watch the video below:
Creating comprehensible insights
What’s most important when deploying a data strategy is: how to create meaningful and understandable insights. Many successful companies have excellent (in-depth) examples of how this can be done, however we also love the work of Hans Rosling. Rosling was famous for the overlooked skill of creating insights. On his website Gapminder.org he explains developments derived from world population developments. All developments were understandable for a large audience:
So, where can these insights lead your company? An inspiring example is Gojek, a digital payment app that used Google Cloud to scale up its solution to Indonesia's traffic problem. Gojek created marketplaces to connect people with different services to Ojeks (motorcycle taxis). Using Google Cloud, Gojek scaled up to 900 times its initial size within 18 months. Today, the company uses its data to let its drivers know where they are needed the most.
How? Gojek has used Google's service BigQuery as the cornerstone of their data foundation, scaling seamlessly to meet their immense data storage and processing needs. Using Pub/Sub as an even stream and Dataflow for unified batch and stream processing has prevented inconsistencies in production data, while simultaneously reducing costs through intelligent resource allocation. Together, these technologies allow GoJek to react immediately to real world events whether by retraining models with ML Engine or by refreshing data in a low latency data store like BigTable. You can learn more about the technical challenges of this project by watching this video. In the video below we conclude with an inspiring overview of Gojek’s journey: