Open Data enables new and innovative business models – There are examples of plenty of innovative business models and lessons coming from adoption of open source technologies and open data standards. These new data harvesting and hosting models are key to stay one-up in the game of competitive advantage. The bottom line is the best inputs (and therefore data) will often come from where you least expect it, and usually over the network (Web or intranet). The lesson: Companies are now critically looking at their traditional data management systems and architectures to build capabilities to establish open data standards and platforms, so that the result will be highly contextual with enriched data for business consumption.
Agile data services at the core of business innovation
The more feedback loops we have and the earlier we have them, allows more accurate and useful course correction. We learned this with agile development processes and we’re starting to learn this with automation in the businesses processes in general. However, at the core of these transformational initiatives, is data-as-a-service. Simply put, the traditional way of managing data and serving data to the consumers is tedious, hence concepts like data-as-a-service, micro services exchanging data and API first approach, are gaining momentum to enable every business become agile business.
Data-as-a-Service facilitating Sense and Respond Systems
The new golden rule is – the organization that has the best data, has the market leading position. This is all the more important and a survival instinct, especially in the context of Digital. The simple economics is that if you are early to sense and early to respond, you have tremendous advantage against your competition. If your data is locked up under the purview of departmental boundaries, you will have a hard time to leverage it. Today’s market leading (and data-centric) organizations deeply understand the strategic value of the data, and don’t let them lie fallow in under-used data silos or locked up behind the firewall. Instead, they exploit them as high value products and offerings, exposing them via well-governed APIs and other strategic means that include tightly integrated business models.
Richer outcomes occur when data consumption outweighs the challenges in data management. It has almost become a cliché that business is not happy with IT, one of the reasons purely from a data needs perspective is – vital business data is submerged in IT systems and databases, when instead, it should be available across the organization. The actual ROI of investments in data systems is not about how effectively you are managing the data, but it is about how timely and cost effectively you are serving data to your business communities for consumption and decision-making. Data must be discoverable, reachable, and consumable for it to have any real, long-term use to the business. Data-centric businesses should focus on lowering the barrier to consumption as far as possible, especially while meeting critical data governance requirements such as, security, scalability, and where appropriate, integrity.
Collaborative decision-making based on democratization of data can generate order of magnitude increase in results. This seems like a bold statement, but the math supports it and growing evidence of use cases in the industry validates it. Central to this concept, is the creation of network effects or establishing a data value chain, where both the publishers and subscribers play a critical role to enrich data at every point-of-service. Collaborative tools deliver this in particular by taking advantage of self-service, data-kiosks and other network-based systems. While it is absolutely necessary to keep an eye on information explosion, but at the same time, it is also critical to enable your knowledge-worker community with tools, and appropriate governance controls to gain rich benefits from information abundance.
Data-as-a-Service is the most powerful business model of all the types of “as-a-service”
We see a lot of examples around Software-as-a-Service (SaaS) and Platform-as-a-Service (PaaS). However in my view, the less well-known Data-as-a-Service (DaaS) is, it could however be the most strategic aspect of creating business value over the network, more than SaaS and possibly even more than PaaS. Creating a best-of-breed set of data assets, wrapping a business model around it (advertising, metering, internal chargebacks, etc), defining an SLA, and then opening it up for consumption for internal as well as external stakeholders, are key to an agile business model. The services could be catering to repetitive business queries or customer facing touch-points or even to serve highly mission critical applications inclusive of compliance and regulatory requirements.
Ease-of-Consumption is the trigger for all downstream outcomes of data-centric businesses
Data-centricity is just lip service if business data isn’t actively made accessible and consumable. The more time and resources it takes to access the data, the more alternatives will be sought, driving duplication in both effort and data. This is why it is all the more a necessity to implement agile data services surrounding enterprise governed data assets. Needless to say that, the new sustainable competitive advantage is owning and providing strategic access to the best set of data. Using all the tools at an organization’s disposal to manage and share data continuously drives a dataset to grow in a virtuous cycle of creating more data, which drives more participation, which creates more data, and so on.
Often I hear the frustrations from business users that they just can’t get the desired data on time and when they finally get the data, the lag has actually made the data obsolete. Out of the 12 CDOs I met last week, 8 of them said “every time there is a business request for specific data, our IT teams go into an overdrive to boil the ocean; the infrastructure is inflexible, data standards are not in place, business glossary around data definitions are out-of-date, etc.”
The more I conversed with CDOs, I found that even if there are agreements regarding how data itself has become the central asset of organization, the focus is far too much on the creation and capture of it, and too little on actively leveraging it and driving consumption.
The popularity of “Data Lake” (an integral component of DaaS) as a novel approach has to some extent democratized Data Management – without worrying about the structure of the data, you can use cheap off-the-shelf hardware and open source software to collect, analyze and deliver data. With DaaS, you can leave behind the familiar challenges of infrastructure, licensing, provisioning, storage management, access management and security, and start concentrating on business deliverables.
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