Corporate culture, an overarching term for the shared practices and values of a company’s employees, guides how the employees of a company act, feel and think. It is also the social and psychological environment of an organisation that symbolises the unique personality of a company and expresses the core values, ethics, behaviours and beliefs of an organisation – not dissimilar to the ideas, customs and social behaviour of a particular people or society.
From a change management perspective, businesses that are transforming their operations through the use of data technology especially, will need to implement a sound programme to interrogate and effect change in its company culture by introducing data culture – a concept that will not only be firmly entrenched in the company’s culture, but also become a considerable portion of its data strategy.
The business intelligence (BI) promise, as often made by BI salespersons, has varied very little over the last 15 years or so.
In the main, it remains that if companies were to use specific methodologies and automation tools to digitally gather data in a certain way and store it all in a common place, the compilation of the data will invariably take less time, leaving more time for the data to be analysed towards improving data-led business decision-making.
In addition, critical data will then be in the hands of all levels of employees to slice and dice transparently for their own analytics and functional needs. Despite the promise, many BI implementations across an array of sophisticated tools worthy of getting the job done expertly, have failed to deliver.
The reasons for these failures, although varied, can often be attributed to an omission of data culture from the organisation’s overall data strategy. A comprehensive data vision will outline the roadmap of data objectives, define the data KPIs and stipulate what data is required.
Specific data projects will support the company’s KPIs and help leverage the quick wins, and carefully chosen data technology will have the ability to collect, store, transform and analyse data in a compliant manner.
All this, however, will not guarantee a successful BI implementation if proper data culture, comprising leadership from the top, enhancing data literacy across the workforce and presenting reward systems and data champions, are not introduced as an integral piece of the data strategy puzzle.
Creating a data culture requires awareness of, and an ongoing focus on, many different elements.
The end-users of the BI solution need a certain prioritisation to mitigate against poor return on the company’s BI investment. The warning factors that most lead to BI implementation failure, as observed over many years of industry experience, may be summarised as follows:
- BI is seen as an IT solution.
- Training was tool-based only.
- Support for business users is limited.
- Solutions deployed replicated reports rather than creating analysis capability.
- Users use the tool to download data and create their own reports in Excel.
- Business/data understanding is siloed in departments.
- Tool usage drops off soon after training.
In contrast, the factors for most successful BI implementations held these attributes as contributors favouring return on investment:
- Business drives or is heavily involved in the BI decision.
- Top management actively uses the BI tool to make business decisions.
- There is a support structure for users from within the company.
- Business users take ownership of their processes and data.
- There are people with an understanding of end-to-end processes.
- Users are able to use the data to make decisions.
- Users are in the system on a regular basis.
Creating a data culture requires awareness of, and an ongoing focus on, many different elements. The details of the framework for creating a data culture will differ from business to business, but the overall elements remain the same.
Directed by an inclusive plan and vision, it will consist of a pre-defined communications plan designed to efficiently and appropriately reach all stakeholders; methodologies for measurement to assess where employees and users are in terms of literacy maturity, tool usage and sentiment and tool adoption; a training and mentoring programme; and lastly, a progress and evaluation process that tracks the difference the solution makes in the various functional areas.
Management consultant and writer Peter Drucker once said: “Culture eats strategy for breakfast.” To be clear, he didn’t mean that strategy was unimportant but instead that a powerful and empowering culture would lead to success.
One of the key goals in organisational development in the last two decades is finding ways of creating cultures that are flexible and innovative, and where individuals take responsibility for results.
To this end, the time and effort ploughed into properly cultivating a data culture will reap the rewards of analytics success and acquire the desired ROI for BI implementations.
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