{"id":1839,"date":"2020-04-15T14:42:00","date_gmt":"2020-04-15T14:42:00","guid":{"rendered":"https:\/\/digiterrebestg.wpengine.com\/?p=1839"},"modified":"2024-05-30T14:21:54","modified_gmt":"2024-05-30T14:21:54","slug":"re-imagining-digital-transformation-during-coronavirus","status":"publish","type":"post","link":"https:\/\/www.digiterre.com\/us\/2020\/04\/15\/re-imagining-digital-transformation-during-coronavirus\/","title":{"rendered":"Re-imagining digital transformation during coronavirus"},"content":{"rendered":"
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Re-imagining digital transformation during coronavirus<\/h1>\n\n

Coronavirus is causing unprecedented change in business and technology at a time when most organizations were already stretched by digital transformation. What does coronavirus mean for digital transformation and what implications does it have for data engineering which lies at its heart?<\/p>\n \n <\/div>\n<\/section>\n\n\n

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Digital transformation \u2013 the use of digital technology to solve problems \u2013 is accelerating due to the dislocations caused by coronavirus.  Whilst it was always part of the effort to increase growth and reduce cost, digital transformation is now more relevant than ever.  However, it is data transformation, in particular, that underpins most digital change \u2013 a fact that many organizations fail to appreciate\u200b.  Given the seismic changes impacting all of us, it\u2019s time to re-imagine the data maturity model, which helps us navigate digital transformation, and re-assess the optimal path through it.<\/p>\n\n\n\n

What is the data maturity model?<\/h3>\n\n\n\n

The data maturity model charts the stages of data utilization within an organization.  We can think of this as a journey with five stages.<\/p>\n\n\n\n

First, in the \u201cno data\u201d stage, there may be very little known or useful data so the organization is unable to run metrics and therefore has no information-based insights.  Business decisions are unattributable \u2013 they literally cannot be attributed to a data source \u2013 and are as good as guesses.<\/p>\n\n\n\n

Moving beyond this stage is a crucial milestone, and a peculiar experience.  As soon as an organization starts exploring its data in the digital age it will experience a deluge of data \u2013 it\u2019s not like opening a tap, it\u2019s more like opening the flood gates.  This is the \u201cbig data\u201d stage when businesses will be inundated with data and need to make the most of the data sources, data silos and scripted transfers.  Contrary to what many believe, organizational decisions at this stage are still based on little or no useful information, so organizations need to progress to the next stage.<\/p>\n\n\n\n

The \u201cquality data\u201d stage is when an organization is able to create standardized sets of data, interfaces and reporting, and corporate taxonomy and metadata.  There\u2019s a cultural shift of organizational behavior where decisions are based on explainable data.<\/p>\n\n\n\n

The penultimate step in the data maturity model is the \u201cpredictive\u201d stage when data is used to make all critical business decisions\u200b and organizations can perform predictive analysis as well as retroactive analysis \u2013 they can predict market behavior.<\/p>\n\n\n\n

Finally, the \u201cstrategic\u201d stage is when data is fully embedded in all business processes and the entire business model is predicated on analytical models\u200b.  No decisions proceed without forward looking analytic data.<\/p>\n\n\n\n

The end point of digital maturity is optimal decision-making that maximizes business value.  Target outcomes include reduced cycle time, reduced defects, increased predictability of delivery, greater compliance with regulations\u200b, improved risk management and reduced cost.\u200b  These outcomes are simultaneously harder to achieve, and more important, in a time of increased uncertainty \u2013 better decisions must be made with greater urgency that may have greater business impacts.  This, in turn, requires the highest value, highest volume, most timely and highest fidelity data \u2013 which means organizations need to reach the top of the data maturity model.<\/p>\n\n\n\n

PROGRESS THROUGH THE DATA MATURITY MODEL<\/h4>\n\n\n\n

Whilst the model may not change, how we address it, and the way we move through it, is already changing.  Agile approaches to software development, which are characterized by the division of tasks into short phases of work and the continuous assessment and adaptation of work, will become increasingly powerful in the new normal.  Previously, managing digital transformation using agile approaches was seen as incidental \u2013 just another tool in the tool box.  Now, it is the only effective way to respond to, and succeed in, a dynamic, complex and unpredictable business environment.  For example, an Agile approach can help identify and achieve quick wins whilst also planning and implementing longer term data transformation, maintaining productivity and staying focused on customer needs.<\/p>\n\n\n\n

Technologists sometimes map digital progress, including the data maturity model, against Maslow\u2019s hierarchy of needs.  Coronavirus has made it painfully obvious that some organizations are languishing at the bottom of the hierarchy whereas others are operating very successfully at the apex.  For example, there are businesses that could work remotely, or undertake key tasks outside the office environment, with the correct planning, but have not done the preparation and therefore cannot operate effectively in the current environment.  Whereas other organizations are operating very successfully in the new climate either because they had robust business continuity plans in place, or because they worked hard, albeit reactively, to set up remote working and distributed teams, or a combination of both.  The crisis has made plain a fact that some businesses only paid lip service to before \u2013 to be truly digital you need to master your data, there are different stages of data maturity, and agile approaches are more relevant than ever to navigate the journey.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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About the Author<\/h3>\n
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Digiterre<\/h4>\n\n \n \n <\/div> \n <\/div>\n
\n Date: 15\/04\/20<\/strong><\/span>\n Category: People Blog\/ Tech Insights<\/strong><\/span>\n <\/div>\n <\/div>\n<\/section>\n\n\n
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