The importance of understanding your data analytics persona

By Dr Sina Joneidy, senior lecturer in digital enterprise at Teesside University International Business School.

  • 1 year ago Posted in

For industry 4.0 and beyond, data processing and analytics solutions will play a pivotal role in generating value streams and creating competitive advantage – and an accurate view of any business’ data analytics capability will provide the foundation for the decisions which power business transformation and future success.


However, for this to happen, organisations must develop data-driven culture. As change does not happen overnight, small steps can provide a pathway for organisations to re-invent themselves as business fit for the future. This will ensure that digital initiatives do not become a back burner when the next crisis occurs.


For organisations who are new to the idea of data analytics as a strategic business tool, a good way to start is by understanding their own data analytics persona. This allows the organisation to learn and understand itself first before investing in suitable technologies to meet its needs. This will avoid a wobbly tower in the future.


This blog will illustrate three different data analytics personas. First, small and medium-sized enterprises (SMEs) with almost no data analytics mindset; second, SMEs with some data analytics mindset (or a pseudo analytics culture); third a truly data-driven organisation.


Any organisation may be either be one of the three or somewhere in between but understanding where you are today helps you build the right foundations for tomorrow.


Persona A: limited capability for data analytics


In this type of business, there is no analytics mindset present therefore, no data processing solution and dashboard is in place.


Chief Digital Officers (CDOs) in these organisations use instinct to plan and pilot digital transformation (DTX). However, they struggle to lift DTX initiatives off the ground and therefore produce results which are aligned with the organisation’s objectives. This is because there are insufficient business operation and marketing metrics in place to gauge their performance across the value chain of which they are a part and, their knowledge of their end customers.


New CDOs in these SMEs often believe that the old method is not working and there is a need for something new. They are not always wrong. However, after 12 to 24 months the organisation replaces the CDO when trouble looms.


In these SMEs when business is doing well everyone gets a free pass but when crisis looms there are no metrics, not enough data or any sort of data analytics program in place to show the progress in evaluating the operational activities and business results.


The SMEs rely on monthly spreadsheets from the bigger partners in their ecosystem to plan production of goods and/or run their services. As such, they do not have sufficient knowledge of their end customers.


The funding process in these SMEs is an annual psychological warfare as top management do not have sufficient understanding of the bright and dark side exponential technologies and make investment in digital “unknowns”.


Despite attending digital accelerator and peer-to-peer workshops, they still find the landscape for funding difficult to navigate and prepare a business case for innovation. The organisation often holds the view “don’t fix what isn’t broken” as the CDO does not have past performance dashboard to justify his/her stand to introduce new measures.


Besides, data analytics does not tick the Key Performance Indicators (KPIs) box for improving the overall productivity and reducing cost in the short run, therefore it is deemed unimportant.


Persona B: some evolution in data analytics


These organisations work with some data processing and analytics tools, consequently some data and metrics are available.


As not all metrics exist, there is no proper data strategy in place to capture them. The organisation might have thought about it in the past and received some consultancy on this, but it became a back-burner, as it is better to invest on what is new and next than to focus on pre-Covid-19 issues.


The team in charge of data analytics has some numbers to cover their initiatives in term of meeting business objectives but from an enterprise-wide perspective, staff are cynical about it.


Unfortunately, investment in exponential technologies happen to just solve the productivity and cost-reduction challenges. Upskilling, training of staff and their data literacy is an afterthought which at best is resolved by registering them in free webinars.


Knowledge of the end customer is confined to partial use of Google Analytics dashboard and its alternatives. In terms of improving business processes there is an unintended compromise between machine learning objectives and business objectives to gain some predictive insight of the value chain they are a part of.


For securing internal funds, CDOs refer the board to improvement in operational metrics as a justification for the next level digital initiative. There are many infographics with elegant pie charts and numbers to gain credibility but whether these data truly reflect the progress of digital transformation is a matter of discussion.


At times metrics are over simplified and over magnified, but the most important data is not there, simply because there is no strategy and courage to capture it.


Executives who approve the budget do not necessarily understand those numbers, no-one knows how to challenge them effectively and they look persuasive.


For securing external funding, they follow the same path taken by other organisations in their sector who have secured innovation fund to increase productivity and reduce cost through Research and Development (R&D) claims.


Persona C – the data-driven organisation


These businesses have what can be considered to be a proper data science program in place.


Metrics are true indicators of their performance. The contribution of their DTX initiatives to revenue generation, societal expectation and environmental protection is calculated with precision. The ecosystem mindset is present. These SMEs do not idolise exponential technologies and data. They are wise and exhibit the right attitude towards society and environment, respecting human tacit knowledge helping them not to lose the power of improvisation and serendipity, to be more than just a “data-driven” organisation with a lot of systematic experiments.


These organisations constantly optimise the personalisation of products and services with the right attitude – i.e. a horizontal relationship with their customers. People, data and infrastructures are tightly knitted across the value chain and the quality performance of each is measured.


A deep-rooted culture which emphasises running systematic experiments helps the CDO to demonstrate the potential values of new products and services to sceptical stakeholders. These experiments, operational, social, and environmental metrics are tracked and monitored systematically, the right dataset is generated, categorised and analysed as a result. The insight is translated to people at all levels.


The financial value, increasing productivity and reducing cost becomes an afterthought. Generating the social, wellbeing and net zero values precedes and gives meaning to the data driven culture and future experiments.


There is an enterprise wide buy-in to invest in the next innovation. These SMEs also find it easier to navigate and secure external funding as the organisation is clear on what it is setting out to do next.


Bringing it all together


In all these three types, “success” of DTX is in the eyes of the beholder. In Persona A, success is very much political. In Persona B, success of DTX is reverse engineered with some data but the majority do not understand it. In Persona C, success of DTX captures every mind and heart that it is exposed to as there is a right data driven culture in place. Persona C SMEs, take a holistic view of what determines success, which is what every organisation should set out to do.


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