Data Management is intrinsic to the change that Digital Transformation symbolizes. Comprising of hard facts about data from collection, unification, quality, and enrichment to maintenance, integration, and dissemination, data management critically influences Digital Transformation.
A recent BCG report showed that more than 80% of companies plan to accelerate their Digital Transformations. If clarity is added to that criticality the study claimed for more than 200 companies, then it can be deduced that digital leaders’s grew by almost doubl compared to digital laggards.
However, as Digital Transformation initiatives reshape one industry after another, why are the success rates less than 30%?
This is because while there may be several reasons to adopt digitalization, the high-stakes world of Digital Transformation seem immensely complex for deep-seated legacy practices.
Consequently, on the one hand, Digital Transformation journeys are either skewed towards ‘woes’ (less than 50% target measures met, no sustainable change) and ‘worries’ (targets not met, limited long-term change).
On the other hand, the ‘wins’ (targets met or exceeded, sustainable change created) are often thought to be unachievable or out of grasp.
The reasons for digital transformation failures could be any (or many). Perhaps it’s the lack of an integrated strategy without clear transformation milestones, or absence of digitally sentient leadership in key roles, or even an organization’s digital immaturity exposed through a truant agile governance mindset.
But, at the end of the day, every operational and analytical infrastructure is finally underpinned by data management.
From insights-based decision-making to productivity enhancements to employee experience and ultimately customer experience for the end-user, it all comes together through a single keystone—Data. Gartner predicts that, in less than a year, 90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.
So, as Data Management and Analytics systems assume the center stage of Enterprise money, minds, and meaning (which are the veritable catalysts of their innovation fuel)—what is really the clear promise of Data Management in Digital transformation?
Simply put, the change management that digital transformation powers in terms of altering attitudes, effective communication, and resilient culture are also powered by data’s ability to bring in tangible, valuable change for enterprises – not just for immediate gains, but also for long-term benefits.
Having established why data management is not just a cog in the wheel of Digital Transformation, but the very engine that propels it, let’s deep dive into the reasons.
1. Reinvents Enterprise Functioning
As wheel-masters of their corporate vessels, negotiating the undulating waves of uncertainty, senior executives must create and communicate transformative vision, establish growth and governance mechanisms, and curate digital-ready culture experiences. All this translates to strategic heavy-lifting married to precise execution rhythms.
This is where Data Management helps amplify enterprise-wide conversations.
- Re-examining internal (and external) use cases with a strong data management emphasis: The point is to leverage digitalization to reframe older bottlenecks through freshly thought triggers.
- Scaffolding and synergizing the Big Three (Digital Vision, Digital Engagement, and Digital Governance) via Data Management: The key here is to combine the iterative elements that drive digital transformations to successful outcomes.
2. Relentless Optimization
On the one hand, the 7 V’s of Big Data – volume, velocity, variety, variability, veracity, visualization, and value – continues to overwhelm corporates. On the other, unreliable data leads to unreliable decisions. To ensure users and stakeholders do not suffer, enterprises have to consistently optimize their digital transformation initiatives.
Data Management systems reinforce such optimization programs by:
- Sanitizing latency in processing by moving away from relational databases to in-memory computing software.
- Consistently exploiting data in real-time by reducing the time between an event and its actionable insights.
- Commissioning digital installations to churn data for enhanced decisions.
Ultimately, data management systems are foundations for digital transformations because the data contained in a company’s single source of truth has to be of high quality, granular, and standardized. The thumb rule is: “Good Data makes for Optimized Processes.”
3. Begets Business Growth
The fact that data is a secret weapon for creating a competitive edge is no secret. Be it via analyses – Sales, Inventory, Consumer, or Competition or via an organization’s ability to harvest data to be in the right place, at the right time, in the right form in front of the right people, these are aspects of competent data management systems.
While the correlation of technology to business growth is reported often, what is not discussed as often is the underlying role of enterprise data strategy.
From a transformation perspective, what does an organization’s data strategy comprise of?
Firstly, data strategy is a plan designed to improve all the ways in which data is acquired, stored, managed, shared, and used.
Secondly, for our current purposes, let’s approach data strategy as a play of ratios. Particularly the ratio of defensive or ‘control’ tactics (compliance, regulatory, risk, fraud, mitigation, etc., by ensuring integrity) to offensive or ‘flexibility’ tactics (increasing revenue, profitability, customer satisfaction, etc. by generating customer insights)
Companies that consistently work this ratio pro-actively and creatively are the ones learning and earning!
In a limited-resource environment, data strategy referees how a data management program will best be aligned for digital transformation.
4. Assists in Strategizing Digital Transformations
Data strategy contributes to digital transformation success by improving organizational efficiency, enhancing collaboration and communication, increasing productivity, and reducing the cost of technology ownership.
Just as the five components of a robust data management program (Identify, Store, Provision, Process, and Govern) help a transformation program maintain its focus on tangible goals, data strategy forces the enterprise undergoing change to identify its strategy gaps and performance leakages in its execution.
Ultimately, data management and digital transformation programs are parallel forces meant to pull existing and future growth levers. Placed and pushed together with equal pressure, the two can technically produce infinite power, or in other words, infinite opportunities for enterprises.
5. Helps Stay Up to Date (Today, Tomorrow, Thereafter)
The final reason why data management programs are a foundation to successful digital transformation can be understood by understanding the very existence of data management, its raison d’etre.
The point here is, the diligence with which an enterprise crafts and conducts its data management program is the same framework it uses to manage its digital transformation initiatives. They share a superset-subset relationship.
The reason why CDO’s, amongst other organizational changemakers and C-Suite executive,s are constantly needed to push the envelope and embrace the latest and greatest in technology is because data management programs, and Digital Transformation by extension, both address an existential question for enterprises.
Data management is crucial for organizations to attain their overall objectives and keep on surging ahead, as data is the very source organizations draw their powers from.
Conclusion
As seen from the prism of a company’s growth trajectory, its stakeholder value, and its innovation agenda, it’s nowhere difficult to connect the themes that unite data management programs with Digital Transformation success.
After all, an enterprise’s strategic choices (i.e., aspirations, my growth areas, measures) will inevitably influence its underlying data foundations (i.e., data culture, my data competencies, data technology) to deliver customer success (use cases, value creation, innovation strike rate).
