While most people can put a list of values on Excel and perform basic mathematical manipulation, not everyone can do an advanced analysis, summarize Big Data intelligently, mine insights that would inform decision making and design interactive KPI-Driven reports/dashboards. It is estimated that only 5% of global Microsoft users are able to optimize the Ms. Excel capability yet this is a readily available Data Analytics tool that most professionals use daily.
The data competency gap in organizations is verifiable through CAN BE diagnostics such as:
1.Percentage of decisions that can be mapped to Data (No Evidence Based Culture)
Many decisions made by line management is through expert opinion (Gut Feel) and only less than 15% of typical decisions are mapped to data. This impacts on strategy execution effectiveness.
2.Regular reporting lags (>10mins)
Many professionals take days if not weeks in preparing regular reports. In our standards, taking more than 10minutes in any regular report is considered redundancy (Whether daily, weekly, monthly, quarterly or annual) Professionals should spend more time in interpreting reports, insights harvesting and undertaking business experiments.
3.Data Cleansing and Reconciliations
Over 60% of the data tasks in highly transactional roles such as in finance, accounting, operations etc. is usually on data cleansing and reconciliations to match entries. This are low value tasks. Ms. Excel Masterly Week & Bootcamp …your purpose led transformation & impact partner… Data to Insights Transformation – Leveraging the power of insight
4.Data to Document Conversion
Many organizations have no clear data pipelines management strategies especially for data feeds coming from documents (Scanned, manually filled etc.). This makes such data being left out in analytics projects.
5.Data Rich Information Poor (DRIP) Syndrome
– Many organizations produce large amounts of data but they do not have a clear roadmap on translating such data in order to become Data Rich Information Rich (DRIR). i.e., Adopt the data evolution path including: Data➔ Information➔ Intelligence➔ Insights➔ Memorable testimonies (Impact Stories)
6.No Data Governance & Data Strategy
Many organizations have not been able to formulate data governance framework and strategies linked to their organizational strategies.
7.Low Data Illiteracy
Organizations continue to invest in Data Tools while ignoring the critical priority on investing in data literacy skills both for individual contributors, line managers and executives. This have resulted to un-optimized expensive BI tools
8.Skew on Transactional Data with no Behavioral Modelling
Many organizations only focus on transactional datasets produced within their organizations and do not include complex human driven models which are majorly Behavioral.
9.Internal Data Reliance
Organizations majorly rely on the internal data housed within their ecosystems such as CRM, ERP, Core Systems etc. while missing out the larger bigdata oceans available out in the world which is majorly unstructured but that has great insights.
10.No dedicated Data Science Function
Many organizations are yet to mainstream data as a strategic resource and therefore, end up having inadequately equipped functional teams handling the data value pipeline which would ideally be a role for data scientists.