Why Considering Data for Operating Model Transformation?

The exponential growth of data, the emerging trends in digital transformation and need for advanced analytics bring tremendous importance for the data and how it influences the organizations business models, capabilities, and the way of working. Data is one of the key disruptions that triggers and drives the need for operating model transformation and is a critical element in designing the Next Generation Operating Model.

Trends and Drivers raising the importance of Data

Data becomes a core asset for enterprise, stands on par with people, technology and capital

Data is no longer limited with the definition of operation data and the performance of the enterprise operation; we see now the changes in IT landscape and raising trends an drivers are putting the data as the core of enterprises business

• Digitization: The rapid conversion of processes, the transformation to digital execution, and the outcomes of intelligent lifecycles are creating high volume of data
• The emerging of IoT solutions and smart systems are bringing massive evolution of the data, not just because the tremendous data sources and data points, but also due to the huge storage, evaluation, and processing required for this data 
• Cloud and Flexible Consumption are breaking the limits for data storage, allowing data to grow in any pace, enabling higher processing capabilities, improving business agility and scalability
• Data Security, Privacy, and Data Sovereignty: With the emerging of data resources and data usage, data protection and governance raised as well to control all aspects of data, i.e. capturing, storage, accessibility, maintainability, usage, ..etc.
• Emerging Data Regulations: new data policies and regulations are defined and designed to reflect government regulations and transparency of data; how it was collected and how it will be used internally and by third parties
• Analytics - A driver or enabler? The trend for analytics was raised due to the availability of data, when combined, integrated, and processed it can give great insights about the business, the market, the customer experience, but now after realizing the importance of analytics the demand for data has increased, this generated the necessity to explore new resources of data, collect as much data as possible, process and combine data to provide advanced and predictive analytics. 

Not to forget the impact of the social media and how it is becoming a strong influencer on enterprise business, brands and customer experience, and is an enabler to generate insights, stimulate demand, and create targeted product offerings.

Recommendations: Data-Driven Operating Model

The emerging trends of data growth and proliferation, and the nature of future of work will generate rapid changes in an organizations’ structure, operations, and processes. Further capabilities and competencies need to be adopted in order to enable the analytics and insights emerging from this aggregated and cumulated data. New tools and processes need to be institutionalized in the organization to accelerate data collection, processing, and orchestration. A governance structure needs to be enrolled to enable data monitoring and ensuring data security and protection.

Data is a key disruptor for operating model transformation, and must be addressed properly in the designing and transformation to Next Generation Operating Model

Because of this huge impact on all the building blocks of the operating model, the whole data elements with its changes, considerations, and impacts need to be addressed properly in the designing and transformation to the Next Generation Operating Model.

Enterprises need to move thinking from basics data generated from internal operations and thru transaction across the value chain, to the thinking of supportive data collected from surveys and market researches, to combined and integrated data with Customer data and business insights.

Enterprises need to move from silo, decentralized data where each department is owning its part with minimum sharing across departments or entities to a centralized data function that is responsible on data consolidation, data analysis, and ensuing shared features to all entities and divisions.

Some enterprises are adopting the role of Chief Data Officer as an evolving role to support the data-driven mindset in the organization.

Some enterprises are changing their business model as a result of data emerging trends and are moving toward an analytics-as-a-service model and therefore are adopting a new data analytics operating model

Data-driven operating model is a key principle for successful way of working, adopting this optimized operating model will enable enterprises to optimize the business performance, build the capability to grow and scale the business, and to generate new values to the market and end users.