.. data was disparate .. collation of information challenging .. required extremely manual processes .. basic monthly reports .. little appreciation of the power of data and insights .. little visibility of forecasted business .. wanted near live updates & ability to see the next 3-6 months ..
.. poor coordination and communication .. duplication of manual Excel data activities .. fragmented and archaic data technology .. lack of deep evidence-based insights .. inconsistent and poorly defined business terms .. all contributing to a lack of trust in data ..
… poor data quality, failing data pipelines .. ineffective & expensive application of data science .. a lack of user satisfaction with the data products .. develop a coherent data strategy and data and analytics capabilities to produce commercially viable data products and insights ..
.. brains trust scattered throughout the business .. coordinate data thinking .. agree and implement a data strategy .. and data and analytics capabilities .. sophisticated audience and consumer insights and predictive abilities ..
.. gain competitive advantage through improved data & analytics capabilities .. change business processes .. pricing and products .. formulate KPI’s and reports .. re-model organisation .. build new functionality of automated matching ..
.. only basic insights .. uninspiring customer presentations .. difficult to interpret. No critical thinking .. lack of communication with customers and company .. limited existing data to mine new insights