By Bill Schmarzo, CTO, Big Data Practice, Dell EMC [NYSE:EMC]
Bill Schmarzo, CTO, Big Data Practice, Dell EMC [NYSE:EMC]
One of the first questions to ask is:
How effective is your organization at leveraging data and analytics to power your business models?
The Big Data Business Model Maturity Index was developed to help organizations understand where they sit today with respect to leveraging data and analytics to power their business models (see Figure 1).
"A smart business entity optimizes the decisions in support of its business objectives"
The Big Data Business Model Maturity Index also provides a roadmap regarding the realm of what’s possible with respect to transitioning from collecting data to monitoring performance and optimizations, to exploiting superior customer, service, operational and network insights to optimize key business processes, uncover new monetization or revenue opportunities, reduce security threats and to create a more compelling, more prescriptive customer experience.
Transitioning From Connected to Smart
The Internet of Things (IoT) is triggering an explosion of sensors and connected devices which is generating a stream of operational, user, and performance data. Buried inside this data are customer, product, service, operational, network and market insights that provide the foundation for utilities to transition from being “connected” to being “smart.”
But what does it mean to become “smart”? A smart business entity optimizes the decisions in support of its business objectives. For example, predictive maintenance would include decisions about identifying at-risk components, what maintenance needs to be performed, what tools are needed to perform the maintenance, when to perform the maintenance, and who is best qualified to perform that maintenance.
Figure 1: Big Data Business Model Maturity Index
To become smart, a utility would seek to leverage the insights about customer usage patterns, product performance, network behaviors and external factors such as weather, traffic, building permits, city and state budgets and economic conditions to optimize business use case decisions such as (see Figure 2): Demand Forecasting, Production Scheduling, Capacity Planning, Network Optimization, Load Balancing, Pricing and Billing, Predictive Maintenance, Disaster Recovery, Revenue Prevention, Fraud, Theft, Cyber-attack, Asset Utilization, Customer satisfaction, Employee retention, Sustainability, and Conservation.
Exploiting the Economic Value of Data
Data and analytics are an unusual currency. Most currencies, such as monetary or human currency, are constrained to a transactional relationship. But data is not constrained by transactional limitations. In fact, data exhibits a network effect (economic multiplier effect), where data can be used simultaneously across multiple use cases thereby increasing its value to the organization.
Figure 2: Smart Utility Potential Business Use Cases
But data and analytics also exhibit another characteristic that no other assets share. Most corporate assets depreciate with usage, that is, the asset gets used up with usage. However, data does not depreciate with usage, and in fact, data appreciates with usage as the data gets more accurate and more complete.
These two characteristics make data and analytics a powerful currency or digital asset in which to invest.The unique economic characteristics of data and analytics pose some critical business and financial questions including:
• How does the utility determine the economic value of its data in order to drive prioritization and investment decisions?
• How does the utility avoid data silos, shadow IT spends and unmanaged data proliferation that thwart the potential value of data?
• How does the utility avoid the disillusionment of “orphaned analytics”?
• How do you re-tool the utility to establish a technical and cultural environment for collaborative value creation?
• How does the utility leverage an asset that appreciates (not depreciates) with usage and can be used simultaneously across multiple business processes?
Fortunately, analytic use cases provide the linkage point to help address the above questions. Focusing on the analytic use cases (and their associated business outcomes) drives the identification, prioritization, capture, development, refinement and sharing of the organization’s data and analytic digital assets (see Figure 3).
Figure 3: Data Lake as the Collaborative Value Creation Platform
Consequently, the data lake becomes the collaborative value creation platform where the data and analytic assets are captured for re-use one use case at a time (see Figure 3).
Utilities operate in a complex business environment, with all the technology, regulation and security challenges. However, utilities are sitting on a goldmine of customer usage behaviors, product performance, network operations and market conditions that they could leverage to transition from connected to smart. Utilities have the ability to leverage the unique economic characteristics of data and analytics to transform their business models—to optimize key business processes, uncover new monetization opportunities, reduce exposure to cyber threats, and to provide a more compelling, more prescriptive customer experience.