Digital Transformation Starts with Solid Data Governance: IBM/NCSU Data Analytics Report Available
We recently completed our 2nd Annual Data Governance, Data Quality and AI Report – 2018. The study points out some important insights for managers who are exploring how to navigate their way through the increasingly complex world of data, which is being accumulated by organizations but which has yet to be really transformed or monetized in a succinct and demonstrable manner. There are many start-ups working on ways to do this, but many organizations are stumbling in their efforts to find approaches.
This is borne out by the results of our study, which shows that there is still significant work to be done around the fundamentals of data governance,before organizations can begin to really reap the benefits of their data assets. The results suggest that a key stepping stone to harnessing the benefits of AI begin with establishing a solid basis in data governance. The results also show that 28% of companies have started some level of engagement in AI which is significant for amerging technology, and 50% of people think it is 1-3 years away.
Data Governance” is the exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets. The basic components of data governance ensure the split of accountability and responsibility related to data thus empowering better decision making while using data from disparate data sources and methods. Data governance provides a system of decision rights and accountabilities for the information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods.
Our study was sponsored by IBM, and also co-sponsored by the Chartered Institute for Purchasing and Supply (in the UK), the International Association of Commercial and Contract Management, and our SCRC partners. Results of our survey suggest that only 37% of companies in our sample actually have someone that is formally assigned with managing data in their supply chain. There is a higher prevalence in software, healthcare, financial services, but sectors such as construction, agriculture, professional services, retail and government have the lowest levels of data governance. By and large, the study suggests that most organizations are still characterized by silo’ed data, a lack of data standards and a lack of skills, making data governance a significant challenge.
Other data from the survey also supports the idea that people are awash in data, and are struggling to find the data they need to make decisions on a day-to-day basis. This raises the issue of Decision Latency: How confident are you in the data that supports your decisions, and how often are decisions made based on no data? Our results suggest that only 15% of respondents feel their systems have the capability to provide the level of trusted data they need to make decisions! Further, the study suggests that over 25% of managers spend more than 2 hours of their data trying to FIND the data they need to make decisions! This is an incredible statistic, and suggests that the ability for managers to quickly access the data they need is problematic, as it often resides in multiple systems, and may not be in a format they need to access it. Don’t believe me? Think of how long it takes to prepare an end of quarter summary report on key supply chain KPI’s. Many managers we spoke with note it can take upwards of two weeks, often involving entire teams of analysts….
The study formed the basis for our bi-annual SCRC meeting, which took place this week at the Talley Student Center. But there will be more on that in upcoming blogs…