What is a “Data First” Operating Model?
Posted in Industry on Jul 09, 2018
The new notion is that data defines an enterprise. What are the new operating models and paradigms that organizations face when their future relies entirely on digital assets? Peter Burris takes a look.
I’m hearing a lot about data gravity lately. What does this term have to do with an enterprise’s data management strategy?:
Let’s look at the ‘digital business’ phrase: rather than treating data as an accessory to its activities, we’re talking about a world where a business treats data as the core asset. A digital business is one that organizes its work around the data, creates new business models and establishes new value propositions based on the data.
Some relate this notion to “data gravity,” which can be summarized as the idea that data attracts more data. In fact, I think it is more valuable to think of data networks, and the way data sources relate to each other and can be combined in new ways.
For example, every system or device can act as a source for new data, and the temptation is to have it contribute to the enterprise data store or data lake, so that the new information can be exploited, analyzed alongside existing data. Many of these systems and devices, though, do not need to connect to each other in a meaningful way, and the data can happily reside where it is most useful.
“I think it is more valuable to think of data networks, and the way data sources relate to each other and can be combined in new ways.”
Taking the data networks point of view, we don’t need to provide all applications and users access to all the data everywhere at all times. This is not practical, necessary or even desirable. However, if we determine an action that provides additional value to customers, shareholders and employees, we need to be able to reach the data, to look for new patterns. In turn, this means that the data must retain fidelity and accuracy if the analysis is to make sense.
That’s more like a data network approach, where we need the tools and capacity to set up and manage data movements and quality, regardless of source and location. Data might be moved from IoT sensors at the edge of the network to the core processing systems, because that’s where the data is required for timely analysis. For the analysis to make sense, the data must be consistent across the enterprise, and always available.
“For the analysis to make sense, the data must be consistent across the enterprise, and always available.”
Who are the fastest movers in the area of data-driven business and how do they think differently?:
Financial services and media organizations place an inherently high value on their data, with retail organizations also recognizing the value that data offers. The places that seem to have the highest need to reconsider the value they place on data are industries that sell products that are now heavily commoditized. Data offers the opportunity to turn products into services, by extending and deepening customer relationships across the entire product purchase and renewal lifecycle.
A classic example here is an aero engine manufacturer. Over time, engine makers have realized that the service and maintenance contract is the more significant piece of business, as it offers the opportunity to work on a long-term, sustainable basis. As airlines seek even greater fuel efficiency, manufacturers additionally realized that the ability to contribute to the airline’s financial performance through better fuel efficiency is more important than the sticker price. Ultimately this leads to “aircraft engine as a service,” where the airline sets performance targets and the data tells both sides if that service level has been achieved.
From aircraft engines to office printers, data has become the differentiating key point of value; and recognizing this change is impacting almost every industry. For banks and financial institutions, data has been central to success for many years. My argument is that this now applies to all businesses: what distinguishes one enterprise from another is the data it creates and controls. If data is the core business asset, then protection, access, security and availability become critical for all companies.
“If data is the core business asset, then protection, access, security and availability become critical for all companies.”
Where does your concept of ‘infrastructure plasticity’ fit with new ways of thinking about enterprise data?:
Until about 15 years ago, enterprises devoted most energy to keeping relatively static infrastructure configurations. For example, applications were resident on specific machines, and networks were sized for current loads, both with maybe some headroom for future expansion. The infrastructure was relatively inflexible, and it could not take additional workload without fracture. But now, information technology is evolving at an increasing rate! Cloud computing brought in the idea of consuming resources on an as-needed basis, and applications were assigned baseline resources with the ability to scale up or back to meet demand. The cloud approach solves the scalability challenge, provided you want to scale existing applications and infrastructure.
The rise in digital business and the idea of transforming an enterprise based on data as an asset – finding new value propositions and creating new business models – means that scalability alone is not sufficient. We need to think about networks of data, how new connections can be made, and how the infrastructure can support different classes of activity that did not exist before. This new digital world requires infrastructure plasticity, capable of taking on a new shape in response to new workloads, able to reach the right data at all times regardless of location.
“We need to think about networks of data, how new connections can be made, and how the infrastructure can support different classes of activity that did not exist before. This new digital world requires infrastructure plasticity, capable of taking on a new shape in response to new workloads, able to reach the right data at all times regardless of location.”
What’s your view on technology that supports – or even drives – infrastructure plasticity?
We want systems that can easily, and with high fidelity, reconfigure themselves in response to new workloads, with the data where it needs to be, when it needs to be there. These are “data-first” systems. Rather than starting with an accounting solution or an order-entry system, for example, we start with real-world events that contribute to the data store, and an analytical model that interprets the data and takes or recommends action.
As we recognize new patterns, create new value propositions and business models, infrastructure plasticity allows us to take on a new shape in support of the business. We need to have technology that ensures data is available where and when it needs to be available, with complete reliability. A digital business must have data assets available to be delivered to applications regardless of potential interruptions, such as outages of specific data centers.
For enterprises seeking to capitalize on data, the ‘live data’ concept is the bedrock of information availability. The live data approach moves away from single sources of data or specific pools that are replicated as ‘master’ and ‘slave’ or ‘backup.’ The live data approach provides a platform of validated, highly available data across the digital enterprise.
“The live data approach moves away from single sources of data or specific pools that are replicated as ‘master’ and ‘slave’ or ‘backup.’ The live data approach provides a platform of validated, highly available data across the digital enterprise.”
For the digital enterprise to be a reality, data must be accessible in a plastic infrastructure kind of way, supporting new workloads that can come online and drive the business forward. Ultimately, business continuity – or even business existence – is tied back to the availability and accessibility of data, and the live data methodology is the route to digital success.