My team and I have been conducting research on what issues business leaders (owners, presidents, VPs, CXOs) have with data and analytics. In our first update the main pain points we saw were around rapid data integration, manual data management, and data translations.
Since then, we have continued to get more feedback and input on pain points, and these results have re-emphasized the need for rapid data integration, and data translation across the board.
Rapid, automatic data gathering has been a key pain point across industries in our research. Business leaders want their data to be rapid, that is to say, they want it to be up to date and near real time. As businesses modernize, having a product report days or weeks removed from the production work costs thousands of dollars in opportunity. Key to making data rapid is integration with data sources (CRMs, ERPs, custom software, warehouse management tools, etc) and automating its flow into one centralized warehouse/lake/pool for analysis and reporting.
Data translation and communication is also a top concern for business leaders. There is less concern about how data was gathered and more concern about what it means and the impact it may have in the organization. Organizations are looking to move past simple dashboards and reports and towards data storytelling. What is the narrative the data is telling about the organization? Where is the company growing or shrinking and why? It is not enough to have data points on a chart, business leaders want to understand the story that brings it all together. Some Bi platforms are utilizing AI to automate parts of the analysis and storytelling as well (see Power BI, Amazon QuickSight).
Other data concern for business leaders include:
- data cleaning and normalization (as one respondent stated, the cloud doesn't save you money if your data isn't normalized)
- handling, sorting, and managing massive data sets
- the expense of data management
- reporting tools that were not set up well and are clunky
- executives managing their data rather than their business
- data integration (with other data sources, hardware, or software)
- lack of expertise to handle the data well
More to come!