All the business models which are data-driven are moved by many organizations through the digital transformation which typically involves artificial intelligence, big data, and predictive analytics technology.
As per the survey, it is noted that the budget which is set for this transformation has already increased this year.
However, many findings are also highlighted by many organizations which report the gap between their investment in this technology and what is the impact on the major indicators that are profits, revenues and customer satisfaction.
For understanding this, 7 capabilities of pivot were identified, when developed or contributed towards a business bringing positive growth through the initiatives of the technology.
It found that higher maturity organizations those who had progressed their digital transformation to the point where they are driving positive growth to deploy an average of 40 initiatives targeting these pivots capabilities, suggesting they are indeed a contributing factor.
Deloitte's chief digital officer and head of innovation, Ragu Gurumurthy, explained that three of these pivots stood out as foundational, and solving challenges around them often opens the pathways to digital transformation at medium and large-sized organizations.
The first things companies should do is focus on data mastery and infrastructure, as well as their talent.
In terms of infrastructure, companies need to create flexible and secure systems that are able to balance security and privacy with the need to flex capacity as business demand changes.
Data mastery is about aggregating, activating and monetizing data that is still often siloed and underutilized in order to generate better products, services and business operations that will drive business success.
Those are the enabling pivots that allow us to begin thinking about transformation.
Data mastery involves generating value from data to increase the efficiency and effectiveness of business processes.
You don't need to own all of the data you just need to know what to do with the data you do own.
What he means by this is while companies like Google and Facebook may have become giants of the digital age by monetizing the data crumbs left by users as they use their platforms and services, not all businesses will need to take this route.
That could mean finding better ways of targeting customers and understanding their behavior and optimizing marketing and retail channels based on the data they collect. In other words, the majority of companies approaching levels of digital maturity where their data becomes a valuable asset is doing so by creating growth for existing, core products and services, rather than creating new ones from their data exhaust.
It's about creating a secure environment, where you can launch applications fast and remove the friction in your operations, and think about how you interact with your customers this is made possible by investing in and understanding your data infrastructure.
The next key pivot talent revolves around the way data is used to understand and nurture a business most vital asset its employees.
This is actually the hardest thing to do. One can figure out cloud migration strategies, one can figure out how to collect and store data, and how to run analytics on it, but its harder to manage change around talent.
If you ask people what their biggest challenges are in digital transformation they will say it is the talent deficit there is often resistance to cultural change and a deficiency in the kind of talent that is needed.
This is challenging because of the different mindset which becomes necessary when transitioning to data-driven business models, particularly when human staff is being asked to put their faith in technology like artificial intelligence and advanced analytics which may result in insights and observations which seem counter-intuitive to many of us.
Its often about retraining the talent another phrase we use is the digital mindset.
It is about the speed of reaction and action, which needs to be faster than ever before. How do people develop products? How do people react to customer needs and run their operations? In every aspect of the business, people need to be doing things faster, think about agile, it's not just agile software development anymore, we now have an agile strategy and agile planning.
It comes down to the speed with which one can leverage data to make decisions and then iterate them creating a self-learning loop that's the heart of the digital mindset. And creating that in the talent is a hard challenge.
Once the foundations of a digital transformative strategy have been built around data master and infrastructure, and talent, then work can begin on the other pivots identified as key to moving towards a mature digital transformation.
These are:
- Ecosystem engagement partnering with external businesses such as tech incubators, R&R companies, and startups to access their resources and talent.
- Intelligent workflows continuously rethinking processes to maximize the capabilities of both, people and technology, and create environments where they complement each other perfectly to deliver maximum business outcomes.
- Unified customer experience delivering seamless and efficient, as well as enjoyable and immersive customer experiences based on a 360degree understanding of customers that is shared companywide.
- Business model adaptability continuously reevaluating and adjusting the business models and revenue streams used by the business.
So, what is holding businesses back from unlocking the full potential of digital transformation? Well, aside from the talent deficiency challenges posed by existing, legacy operating models, and a lack of a strategy for clearly prioritizing adoption of transformative technology were cited by 49% and 45% of respondents, respectively.
And while organizations in the technology, media, and telecommunications sectors were the most likely to have reached the level of maturity that brings bottom-line growth, one surprise was that, once they have made the grade, benefits across all sectors are broadly similar.
Source: HOB