What is needed to make digital transformation work? [Q&A]
Digital transformation is a topic that's been in the air for more than just a few years now, but the impact of the pandemic and the need for businesses to adapt has rapidly brought it back to the forefront.
It's also no longer just about IT. Digital transformation is an enterprise-wide endeavor, connecting and affecting all business units and requires a shift in mindset to take full advantage of the opportunities it offers.
So, what makes a successful digital transformation initiative? And how do you know if you're on track? We spoke to Curt Anderson of enterprise performance management specialist Jedox to find out.
BN: Why is digital transformation suddenly on everyone's mind?
CA: Digital transformation has been a buzzword for years now. In fact, you can find its roots in the development of the microchip in the 1950s. Later in the 1980s automation started to enter the workforce. The pandemic and its ensuing challenges have lifted the term to new heights. Ultimately, the goal of digital transformation is to heighten efficiency and effectiveness through the optimization of business processes with the use of technology, no matter the industry. Every organization has unique needs. While a manufacturer or retailer may struggle with supply chain issues and logistics, a sales organization might instead need to focus on strategic sales planning. Either way, speed and scale are key factors in considering the right tools to apply to an organization’s digital transformation journey.
BN: What type of mindset does a leader need to drive a successful digital initiative?
CA: A leader driving a digital initiative needs to have an overview of the organization. Automation for automation's sake doesn't benefit anyone. Consider which repetitive, manual processes that are error-prone and redundant can be replaced with automated ones. Identify which existing tools you have to make that transition possible. Digital leaders who excel at uncovering redesign opportunities rely on four key techniques:
- Design thinking: taking a people-centered and journey-based view to optimize processes that account for human empathy as well as analytical criteria
- Process clean-sheeting: designing an optimal process from scratch rather than making incremental changes to an existing process
- Role-level assessment: analyzing type and hierarchy of roles within the organization or function when evaluating the potential for automation
- Minimum viable product: developing a new process that addresses the most basic criteria via agile sprints and rollout in releases every three to four months to test and adapt in the marketplace
BN: What are the three levels of digital transformation maturity specific to financial planning and analysis processes?
CA: It is noteworthy to mention that every organization can embark on their digital transformation journey no matter where they are right now. The three levels of maturity for FP&A processes are:
Maturity level one:
Manual-based planning processes are common in which the organization relies solely on manual input through tools such as Excel and, yes, even whiteboards.
Maturity level two:
A hybrid of manual and digital processes through automation and collaboration in which the organization uses a blend of both automated data updates, but also manual processes that could be automated, but have not yet been.
Maturity level three:
A strategic enhancement of planning processes enhanced by modern technology such as Artificial Intelligence supports full-scale digital transformation in which the organization has eliminated manual, repeatable tasks to allow more value creation.
Many manual processes are truly antiquated. At the same time, technical improvements through digitalization itself do not add sufficient business value. In order for genuine digital transformation to occur, planning processes must be based on collaboration, business logic, and data integration.
BN: What does it mean to have a data-driven culture? How do you go about creating one?
CA: A data-driven culture refers to a company’s ability to analyze, interpret and execute programs and processes based on existing data in order to make informed business decisions. It also means decision-makers rely on real-time insights to drive business performance. Relying on predictive analytics for accurate forecasting is an example of this.
Executives understand the need for digital transformation. According to a recent Gartner report, 69 percent of board of directors claimed they saw an accelerated need for digital transformation due to the pandemic, yet another Gartner study stated only 40 percent of companies had actually reached that goal. A 2020 Deloitte study underscores the fact that digital maturity leads to higher business performance. Leaders are now tasked with getting employee buy-in to drive a data-driven culture by offering upskilling and reskilling programs to bring along the workforce into the digital age.
BN: What roles do AI and Machine Learning have to play in the digital transformation journey?
CA: AI used to be a thing of science fiction. But now we use it nearly every single day. Just think of voice recognition technology as an example: Hey Siri! According to a late 2021 report from PWC, 86 percent of those surveyed claimed AI is now viewed as a 'mainstream' technology. Those who adopt AI and ML solutions in 2022 will see higher revenue growth compared to those who cling to their manual processes. In terms of data preparation, forecasting, and simulations, vendors of modern finance management tools have identified the need for better accessibility to AI solutions. The same thing applies to Machine Learning. To go back to the microchip example from the 1950s, AI and ML are rapidly becoming an integrated part of our daily lives. Digital transformation is a journey, much like life itself. The destination is changing as fast as the market demands. Those organizations that wish to keep pace with the evolution will embrace the journey with open arms.