Congratulations! If you are an innovation and technology decision maker at a large enterprise, you have more than likely passed through your first phase of digital transformation: Your IT infrastructure has mostly or all been moved into the cloud; your tech is playing nice with one another – or at least nicer than the days of swivel chair integration; decisions happen a bit more efficiently; and you’ve survived one-and-a-half years of remote work with beginning plans for how you’ll approach the changing dynamics of the workforce over the next several years.
Now it’s time to be ramping up to the next phase of digital transformation and facing the next paradigm of business with clear eyes, even if there are a lot of unknowns. Whatever the future brings, it’s exciting, and you will need to be increasingly more flexible, agile, and decentralized while still managing the day to day of your core business.
Everyone’s well aware that there is an enormous competitive advantage to having deep data sets, but the question is, how will you increase your ability to optimize for big data and use it to its fullest advantage so that it is actionable and accessible? How will you balance innovation with risk and regulatory factors? You’re facing all of these challenges and opportunities with strong considerations for ramped up cyber security that meets today’s increasing threats.
So, what are the biggest priorities now for the large enterprise? Here are 7 of the most important spokes on the Digital Transformation wheel in this next phase:
- Shifting to a hybrid of edge and cloud computing that taps into both centralized and distributed storage advantages. As we describe in detail here, edge computing allows organizations to streamline data so they can act quickly and nimbly, implement machine learning, increase privacy, and a lot more. On-premise edge computing lets you act on real-time data but still offload heavy computation responsibilities to the cloud at regular intervals.
- An investment in smarter predictive analytics that allows for real-time data to be used effectively in smart devices (hardware) and sensor tech-enabled IoT software. Through the use of statistical techniques such as data mining and machine learning, more sophisticated predictive analytics modeling analyzes historical data to predict future behaviors which helps you pinpoint the right actions for more optimal outcomes.
- A laser focus on interoperability. Though easier said than done, the aim here is to not have gaps between the technologies you employ across your organization. This is a long-term goal but there are things you can do to offset the challenge of deeply embedded legacy software coming up against new and better technology. Investments in more intuitive custom software development should work to align departmental goals and facilitate more seamless company, employee, and customer communication.
- Implementing a program for the continuous upskilling of your workforce. As AI and robotic processing grows in prominence and roles demand a different knowledge set, different hardware, and more hybrid workforce models, you’ll want to develop software your team will readily adopt and grow with. You’ll also want to build processes into operations and overall structure of the company that account for these efforts.
- In HR, training used during the employee onboarding process can utilize emerging technologies that make use of immersive experiences to create a realistic learning environment and improve skill retention while measuring and managing performance with better tools.
- Speaking of employee development, HR is undergoing its own transformation, taking on board a shifting employee mindset: employee as customer. Your digital transformation should include personalized HR tech that bolsters inclusivity, work-life balance, and flexibility – all while keeping data secure.
- Finding the right balance of internal teams and well-aligned external partners to support and augment your efforts and hypotheses. Finding the right partner to do that will disrupt the echo chamber and get a deeper behavioral perspective on business outcomes. This is key to phase 2 digital transformation.
Overall, it’s an exciting time to assess how far you have come in preparing to scale the digitalization of your business and what you need to do to prepare for a tech enabled end-to-end delivery system that makes room for big data, real time connectivity, machine-to-machine learning, AI, robotics, and an increasingly immersive work experience. It’s a great time to be at a forward-thinking large enterprise.
