Digital transformation is more than technology adoption

THE DIGITAL DIP

The secret to success is carefully treading the tight rope between technology upgrades and sweeping operating model changes.

Each needs the ideal balance of attention. Too much focus on technology and too little on the operating model will, after initial success, land the enterprise in the middle of a digital dip. This digital dip is typically caused by a siloed approach, limited ability to glean meaningful insights from data, transformation fatigue, KPI confusion, conflicting stakeholder views, and poor user adoption. 

The best way to avoid the digital dip? Remember success across the breadth of the enterprise is the objective. For results that stick, technology transformation must be driven by a comprehensive IT and operations framework rooted on agility, analytics, automation, and cloud. Keep everyone in the know and provide a clear roadmap, success metrics, and objective. Everyone in the organization must be on the same page armed with the same information and driving toward the same goal. Collaboration, training, and feedback loops are important too. Foster an environment where everyone feels their voice and observations are valued, considered, and acted on.

THE FOUR ELEMENTS

To create future-ready operations, an integrated approach is essential. This has four elements:

1. Integrate operations across IT, infrastructure services, and business processes. 
2. Use automation to take over routine, manual tasks and processes. 
3. Extract actionable insights from data generated by these automated processes. This is best done with a machine-first approach, conserving human efforts for complex tasks that cannot be automated. 
4. Identify process disruptions, and prevent/correcting them.

The insights and automated tasks enabled by this shift will further introduce technologies that can make processes faster, more accurate, and less expensive.

To embrace a cognitive and integrated operations approach, switch from being process-centric to being data-centric. 

This means automating not just the operations, but the delivery of insights. Machine learning, AI, and advanced analytics capabilities can today be used to identify and fix inefficiencies without having to overhaul the entire business operations.

Filling orders, responding to customers, and ordering supplies can—and should—happen without human intervention. Systems supporting a cognitive operation can also provide alerts that predict problems before they occur and provide insights to perform tasks that machines cannot. 

GET AGILE

Business transformation requires cultural change, access to differentiated talent, a plan to upskill existing talent and, most importantly, long-term commitment.

Governance is critical and enterprises need to measure value through evolving metrics. 

Be agile, innovative, and forever evolving: 

• Majority of enterprises believe organizational structure is a barrier to digital scaling. 

• Digital command centers play an active role in enterprise-wide adoption and scaling of innovation. 

Have flexibility, balance risk, and innovate: 

• Rapidly iterative and adjusting journey cycles will help balance risk and boost flexibility.

Foster ownership, experimentation, and collaboration: 

• Ownership-driven culture with focus on experimentation. 

• Leadership buy-in for cross-stakeholder alignment.  

• Achieve collaborative innovation across silos and iterative improvements.