Multi-device approach to deliver timely and contextual IP intelligence
May 14, 2014
May 14, 2014
Some of our recent efforts have been directed towards developing a multi-screen approach to delivering Intellectual Property (IP) intelligence to various stakeholders within an organisation, via the Relecura platform. Relecura achieves this by employing an integrated approach involving complementary applications built for the web, mobile, and using its Application Programming Interface (API).
The motivation to engineer this kind of a platform comes from the fact that the manner in which we get our business intelligence, make decisions, and action them – has changed with ubiquitous connectivity and the proliferation of smart devices. This trend was initially signalled by the fragmentation in the consumption of digital media over multiple devices. This necessitated the adoption of a multi-screen approach by various large media companies.
We see this now happening in the enterprise as well – none more so than in the delivery of Business Intelligence (BI), where enterprise applications are accessed using a variety of devices, for information and data analysis of various business functions. Different individuals in an organization have different contexts and requirements for decision making using business intelligence, including that related to IP.
IP intelligence is accessed at various times, on different devices, and for different purposes. The IP intelligence delivered must be tailored to the device, and be both timely and contextual with regard to each individual’s task and role. Information and data should ideally be “pushed” appropriately to the relevant individual, rather than the person having to “pull” or search for it.
Furthermore, the impact of IP is now greater in strategic decision making. Hence applications that deliver IP intelligence need to be more tightly integrated with the other enterprise Decision Support Systems (DSS) of the organization. Hence there is a need to engineer an IP analysis platform with an architecture that lends itself to this workplace reality.
We see the above trends stated in industry reports. Some of the key trends are listed below.
– BI systems have traditionally been highly centralized. Reports are generated from a central source and then disseminated to various groups and individuals in the organization. They have not traditionally been widely used by a broad cross-section of business users within an organization. There is now a move to make BI more accessible and pervasive and go beyond traditional reporting scenarios.
– An outcome of the above is that BI is being more widely used within organizations for a variety of use cases such as ad hoc querying, data discovery, and analytics.
– Along with traditional reporting, BI platforms are embedding dashboards, analytics. These elements are being made available in other business processes and applications.
– The ease of use of analytics apps, especially on mobile devices, broadens the base of BI users to include those who in the past may not have used such systems for their business decision making.
– Increasingly sophisticated analytics engines are being built into the BI platform with predictive and prescriptive capabilities, using new types of data and analysis techniques.
– Collaboration, sharing of analysis reports and annotations, real-time discussions via forums and chat – these are a common thread and implemented across the BI platform.
Let us now look at IP specific use-cases for each of the access modes.
– Data consumption via dashboards.
– Ad hoc queries – quick searches.
– Save and share search sets for detailed analysis to be done later.
– Interactive data visualization. Run some quick what-if scenarios.
– Getting contextual alerts.
Most of the heavy lifting will be done here. This will be the access mode of choice for the patent analyst. Some typical use cases are given below.
– Workflows involving comprehensive search and refine operations such as prior art search and technology landscaping.
– Large portfolio analysis and management and related workflows such as bucketing, gap analysis, portfolio comparison, and competitive analysis.
– Interactive visualization.
– Advanced analytics – such as trend forecasting, developer support.
– Transaction analysis for IP commercialization lead generation.
– Creation of customized dashboards, which are then shared with various individuals in the organization. This will be contextual based on their specific role and function.
– Setting of relevant alerts to be pushed on a contextual or need to know basis to specific individuals.
The web is getting increasingly “appified”. Most of us have installed either apps or widgets on our devices and web browsers. These slices of the web deliver a key subset of the functionality and data of the cloud based application. One can think of stock tickers and e-commerce mobile apps in this category – among many others.
These widgets and apps are built using APIs provided by the online platform. APIs help in growing a healthy 3rd party developer ecosystem that creates apps for a particular platform.
IP specific examples of the use of APIs are given below.
– Depending on the data and functionality exposed via the API, increasingly sophisticated apps can be built that deliver not just data, but interactivity and the ability to execute transactions.
– In certain cases organizations may have specific needs with regard to IP analysis and intelligence, in which case there is a need for an API set that facilitates rapid application development.
– Increasing integration with other enterprise apps, since IP is getting more embedded in strategic business workflows. This again needs a rich set of APIs.
IP has become deeply embedded within modern knowledge-based organizations. IP today is no longer the domain of just the IP group in a company, but impacts individuals with various roles – from decision-making by managers to new product development by engineers. IP is of significance at every stage of the product life-cycle. There is hence a need to democratize the access to IP intelligence and make it available to even the ordinary business user. We believe that a multi-device approach to delivering IP intelligence is a suitable means to deliver IP Intelligence to various sections of the organization in this evolving scenario.
The above approach along with relevant use cases, was recently presented in a workshop at the PIUG 2014 Annual Conference, 26 Apr – 12 May 2014.
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