Based on my observations, and an initial analysis* of respondents who have participated in our interactive Enterprise Data Discovery Maturity Model, the answer is no. (*58% of respondents are classified as being average - “Connectors” - or below average - Isolator - in their ability to exploit the value of their business data.)
So how can business train to be better at analytics? Data.
Data makes the difference between an average company and a high performance organization – but only if it is processed properly. After all – every organization has data, but only those that are analyzing and sharing insight based on quality data are creating business value. In fact, a recent report from McKinsey states that sectors such as finance, manufacturing and professionals services stand to make great gains from big data – if they can harness it properly.
For too long, organizations have focused on integrating technology – and they have hit a brick wall because it’s too difficult (if not impossible!).
Elite businesses have taken a new approach and have focused their efforts on bringing together and transforming data into actionable information so it can be used in existing reporting systems and tools.
By effectively extracting and analyzing the data traditionally locked down in disparate silos, knowledge workers are able to obtain a crystal clear view of their business – often for the first time, and use these processing capabilities to power ahead of their peers.
Data has to be the first step in any business intelligence project. Decision-makers need to use technology to enable them to leverage their data to provide the insight to inform business decisions.
Elite companies have established processes that standardize the collection, integration and transformation of data so it is useful for knowledge workers.
For your business to do the same, you should ensure your data follows five proven processes:
Extraction – Elite companies have tools which effectively extract, transform and load data into their chosen system for analysis, bringing data from across platforms and silos into a single data pool.
Categorization – To make sense of data, it needs to be classified in an intelligent, efficient and relevant manner prior to and during analysis.
Enrichment – External sources of information are then added to existing data to improve the quality of analysis. This enrichment provides valuable insight in areas such as supplier risk.
Analytics – The data is now ready for analysis in easy-to-use dashboards and reports. These analytics empower business users to get answers to their most pressing questions without having to rely on IT to create and maintain reports.
Collaboration – Data fuels thinking and better decisions when insight is distributed amongst colleagues. It is standard practice that dashboards and reports can be easily shared, unlocking the initial value of data.
By ensuring each of these processes is in place, you will have the data – always accessible in any reporting tool or system – to outperform your peers.