The amount of data is increasing exponentially. Even though data is all around us, only a fraction of companies truly know how to utilize it. Studies show that there are major benefits in transforming into a data-driven organization: such organizations experience increase in revenue and decrease in operating expenses.
Robin Andersson, Nordic Information Integration and Governance Lead at IBM, speaks about the various possibilities of data and analytics. Below Andersson shares his advice on how to become a data-driven organization and reveals four success factors. Where does your company stand? Are you data-driven enough or yet to start your journey?
How are companies utilizing data?
Many organization have a long way to walk; a recent IBM Institute of Business Values report indicates that approximately half of all C-level executives make business decisions on inaccurate or inadequate data. This is contradictory to another IBM report “Inside the mind of Generation D”, where seven out of ten respondents say they aren’t lacking data. The key to driving business value is how enterprises use data and sophisticated analytics.
One of the main challenges facing organizations today are data siloes, which limit access to data and sources. In addition, many of the tools in place are anything but easy to use, making it harder to put analytics into action.
What does it mean to be data-driven?
Behind the success of data-driven organizations there are four common characteristics: data is centralized and organized, data governance policies are in place, and both data and analytics access is integrated into tools.
1)Data is centralized and organized. To ensure that data is recent and relevant, data-driven organizations gather data from across the organization. Don’t limit data gathering to internal sources; there are multiple external data sources that can, and should, be included in analytics (depending on the industry). Be aware of what data and how much you gather – information overload is a real threat. Today, many companies are establishing data reservoirs with a combination of internal and external data. However, it is important that data flowing into the data reservoir is strictly controlled in order to reap the desired benefits of the investment. A key guideline? It’s not about size – it’s about data variety.
2)Data governance policies are in place. To safeguard the quality of key master data objects like product, customer and supplier, there should be clear data governance processes in place. According to Gartner master data quality deteriorates at a rate of 2 per cent per month if not governed. Master data quality is the key to high quality analytics.
3)Data is accessible. In data-driven organizations everyone has access to some data and only a few has access to all of it. Data security and privacy requirements limit what data can be accessed. Everyone should have access to data, which is required to perform their job, and data should be easily accessible via different tools, such as smart phones, desktops and laptops.
4)Analytics is integrated into tools. Data-driven organizations tend to have highly innovative analytics tools, which facilitate defining analytics models. They are also embedded into existing tools, making them more likely to be used. Competitive advantages arise from analytics models, which allow users to predict and act upon business insights and thereby optimize outcomes. When analyzing data, organizations should always start with a business question.
Where can companies start the transformation?
Rule number 1: don’t undertake massive changes! First, start to collect and look at your data; it’s the fundamental building block and you cannot answer any business question without it. Secondly, transform the organizational culture and empower your people to access data and encourage them to use it – even with self-service. And thirdly, don’t overengineer data models.
In order to accelerate transformation, you can appoint a Chief Data Officer (CDO). A CDO can take on different responsibilities, but in general the CDO drives the data agenda and owns the group-wide strategy. Roles and responsibilities should ideally be clarified before the role is implemented to avoid treading on anyone’s toes. In US, we now see an increase in the number of appointed CDOs among IBM clients. How quickly will other countries experience a similar pattern? After all, data is today’s most important enterprise asset, yet not fully utilized.