Companies need to prioritize data transformation over digital transformation if they are looking to be data-driven.
In a digitally empowered age, businesses across the globe have grand ambitions of leveraging the power of AI, big data, and machine learning. Innovation is happening at a rapid pace. Companies are investing millions of dollars in building data lakes, moving to the cloud, hiring data scientists and chief data officers to run their digital transformation plans.
Yet, they fail. Spectacularly. Plenty of reports and surveys show that over 85 per cent of big data projects are failing with varying causes.
Enough has been written lately about how business cultures and unchecked ambitions lead to big data project failures. This piece will focus on how poor data quality is often overlooked and makes for one of the leading cause of digital transformation failure.
Data transformation, the process of transforming raw data into a usable format is often, incorrectly, juxtaposed with digital transformation. Companies assume that because they are implementing data lakes, data centres or new ERPs, (which are all part of digital transformation), they are transforming their data.
This is a dangerous assumption. It takes the focus away from the real problem and gives companies a false sense of security. New systems are expected to resolve problems and help achieve transformational objectives but fails to do so.
The new ERP your company implemented six months ago, does not boost operational processes because data issues in the legacy system were not addressed. The new CRM your marketing team invested in to get in-depth customer insight doesn’t return the expected ROI because the team does not have data governance or data quality framework in place.
Understanding the difference between digital and data transformation can save a company from making costly mistakes. If organisations want to be data-driven, they have to start by understanding their data, fixing inconsistencies & transforming their data. Digital transformation is the end of the process – data transformation is the start!
We’ve worked with Fortune 500 clients who prioritised digital transformation only to find out their data was not ready for it. Some of the most common issues usually are:
Poor data, bad data or dirty data is data that is the result of all these causes. Over time, poor data becomes an emergency, a security breach, a disaster that can break your business
An old but still relevant Gartner report revealed that at any given time, poor data quality is a primary reason for 40 per cent of all business initiatives failing to achieve their targeted benefits. Although a decade old report, this research still stands its time. Today, as organisations use on average more than 400 applications at any given time, data is constantly streaming in, most of which is raw, dirty and unusable.
Managing this data and ensuring that your organisation has data it can trust is a regular job, one that everyone in the organisation should perform.
And herein lies the answer to the second part of this question.
Business leaders overlook data quality problems because for eons now, data is considered an IT responsibility.
Almost every data issue is itself siloed away in the IT department. Business leaders, including C-level personnel, are either unaware or uninterested in resolving data quality issues. Compared to other grand transformation plans, data quality issues are seemingly so inconsequential that it’s completely overlooked by decision-makers. Of course, until the transformation plan is stalled or fails and again….the IT department will take the blame.
This disconnect between IT and C-level suites is the fundamental reason why experts cite, ‘company culture’ as one of the leading causes of transformation failures. For an organisation to be data-driven, the responsibility has to be shared by business teams.
Because new technologies depend on accurate data. Whether you’re creating the next generation robots or whether you’re banking on big data to understand your audience – you need data you can trust.
Data transformation, therefore, becomes the means of achieving the digital transformation goal. As in our experience, companies that actively transformed their data and implemented data governance in place were able to increase their ROI, optimise their operational processes, make valuable use of their workforce & eventually were able to transition into a digitally empowered enterprise.
The conclusion is simple – to be data-driven, you need data you can trust. To get data you can trust, you need to implement a data quality framework.
Originally published here.