BusNostics

Not only does businesses fail at incorrect positioning, misread changes and gaps in the market, and misplaced capabilities to deliver on their niche, but they fail in the translation of the big idea into executable goals, measuring against these, and making appropriate course corrections.

The hype of digital transformation to radically enable businesses, from 2010 to 2020, and the AI hype of removing people from business processes 2025 and beyond, is not translating to more than a few businesses. The reasons are well studied. Books such as “The Technology Fallacy – How people are the real key to Digital Transformation” identify enabling people through physiological safety, free to experiment as the key enabler.

“Data” is such a misunderstood topic – in the article of https://www.jeffwinterinsights.com/insights/digital-transformation-framework-ppt Jeff Winters postulates that the golden triangle of “People-Process-Technology” is incomplete, and I quote:
Leadership and vision—core aspects of the People pillar—are now more empowered than ever by data. Leaders with clear, data-driven visions can effectively communicate and align teams toward a common transformation goal. Collaboration and communication across the organization are also enhanced by data-sharing, breaking down silos and encouraging cross-functional knowledge flow.

On the technology side, the focus is no longer just about implementing tools—it’s about building robust infrastructure and embracing technologies that allow seamless integration of systems. The convergence of people, process, and technology is only possible through strong data infrastructures, agile methodologies, and cybersecurity measures that protect the systems from potential threats.

Most organisations the author have worked with – including where he have worked in large multi-national companies – have implemented great tools such a PowerBI online, and the governance to enable report viewing, but were not able to build the supporting data infrastructures where business processes can easily use master data and to create enriched data sets to speed up the understanding of the effectiveness of a process, for improvement there-of.

In the author’s opinion, the reasons for this includes that most business people and those they employ to operate business processes, are not trained on the beauty of data domains, their structures, relationships of data, the impact of understanding data patterns, the contribution to your data infrastructure when data is built from atomic levels upwards, the major contribution master data can make to bringing disparate business and process domains together to see business patterns.
Then adding insult to injury – most companies will have some sort of ERP / billing / customer management system – but with data theft (or perceived theft) being so easy – is deemed non-sharable to the “digital shop floor” where the real work is done, with the effect that islands of data are created by such process owners – recreating business data in a different way, which renders cross domain data insights impossible.

Furthermore, the state of a business or sub-domains that needs attention, needs to be read in the context of its developmental phase – as business constantly morphs – impacted by constant changes to factors described by PESTEL that will force constant dynamism on the business, new opportunities and threats will arise – with the business always behind to try respond to that. Org structures, people capabilities and governance mechanisms are always in catch-up mode to the ever changing business landscape. This then causes systems ℗ople, processes, technology, data) – specially where they are needed most, to be lacking – not supportive of decision making, not giving early leading KPIs to steer with.

The idea with “business diagnostics” is not to boil the ocean – to tell corporates how broken their people-process-technology-data infrastructure is – but to assist to prioritise which steps to take to make fast improvements in business.