diwo: a cognitive system for continuous business optimization
diwo® is a platform developed by Loven Systems for supporting analytics-based decision-making in businesses with novel cognitive capabilities, in order to enable continuous business optimization. The design of diwo is based on patent-pending methods built around the concept of an opportunity and cognitive decision-making methodology, called SEAL™ (an acronym for Sense, Explore, Act, and Learn).
Informally speaking, an opportunity is a time-sensitive business situation that, if not addressed in time, will have an adverse impact on the financial performance of business due either to missing potential gain or by potentially incurring a loss.
diwo reveals business opportunities in real-time by continuously analyzing incoming data streams from various sources. It explains the potential impact of revealed opportunities, further recommending a best strategy to address the opportunity within the current business context.
Furthermore, diwo also provides flexibility for decision-makers to explore alternative strategies by tweaking certain decision levers. Once a strategy is approved by decision-makers, diwo provides a list of tasks that can be carried out to implement the strategy.
diwo® as a cognitive system
The design of diwo is inspired by the hypothesis that in today’s open, hyper-connected, super-quantified, and rapidly changing business environment the only way for survival and growth is the “Cognitive Way.” The cognitive way brings automated intelligence to bear upon the decision-making process.
Whether we admit it or not, the human cognitive ability to make effective business decisions has been surpassed by the growing complexity of business, in which simply making gutsy decisions based on individual experiences is fast ceasing to be a viable option.
diwo enables businesses to transition from courageous business decisions to smart business decisions by enforcing a systems-thinking mindset, through augmenting human cognition and striving to continuously optimize the financial performance of the business. In diwo a business is reimagined as a cognitive system whose sole purpose is to optimally respond to opportunities under certain well-defined types as quickly as they arise.
A business operates in a space of opportunities. Given the various aspirations and resources at hand, not all opportunities may be viable for a business at any given time. Moreover there exists a vast space of available opportunities that slip by, because there is no ample time to react. These opportunities are revealed either too late, or never at all.
Continuous business optimization works in two ways: first through enlarging the space of addressed opportunities by revealing them on time, and second by providing guidance to address them in the most profitable ways.
A cognitive system is any system that exhibits a certain level of intelligent behavior, as evident from its cognitive responses during interactions with its environment. There are various levels of cognitive ability, ranging from the reflexive level (the lowest level) to the self-aware level (the highest level).
Intelligent systems differ in their cognitive ability and not all tasks require the highest forms of intelligence. The best approach is to imbue the right level of cognitive ability for the task at hand. diwo is a cognitive system which exhibits intelligence up to the fourth level for real-time business decision-making.
diwo’s cognitive ability is evident from its three personas which support three different –but complementary– forms of interactions with decision-makers.
diwo ASK’s persona supports goal-directed guided conversations based on patent-pending technology from Loven Systems. Decision-makers can converse with diwo in natural language (only English is currently supported) using either voice or text. diwo responds in a multi-modal manner by using voice, text, and interactive visualizations.
In contrast to simply answering a question posed by the user, diwo applies deliberative intelligence to understand the problem that the user is trying to solve. With that understanding, diwo produces better answers and gently nudges the user towards solving the problem faster. diwo also learns from user interactions and has the ability to adapt to individual problem-solving styles.
diwo DECIDE’s persona supports guided continuous business optimization by revealing opportunities via automated intelligence, and by guiding development of optimal strategies. diwo builds user trust by providing explanations and evidence for its recommendations, while also allowing users the freedom to explore other options. Besides using domain knowledge and continuous learning, diwo DECIDE works behind the scenes, using advanced analytical methods appropriate for the specific opportunities available from the repertoire of descriptive, predictive, and prescriptive algorithms. diwo DECIDE is configured with the appropriate domain ontologies for all the opportunity types it handles. These ontologies can be edited or augmented as new opportunity types which are introduced to diwo.
diwo WATCH's persona supports continuous observations and a fast decision-making mode for routine and less complex operational decisions. These observations alongside on-the-fly streaming analytics are provided in “always on” and “always available” visualizations through browser and mobile application interfaces.
diwo® as a reactive distributed software system
As a software system, diwo is a reactive distributed system comprised of many intelligent sub-systems, which collaborate with each other to create a cognitive synergy–yielding intelligence that is far beyond the reach of a single sub-system.
diwo software design follows the reactive manifesto and all its components are responsive, scalable, resilient, and even-driven.
diwo uses a micro-services architecture realized by asynchronous communicating actors supported by AKKA concurrency toolkit, Lightbend, and Scala. diwo comprises 10+ actor systems which run concurrently to provide its core functionality.
User interactions are handled via Play Server while the front-end is written in Angular.js, Material.js and D3.js.
Front-end and back-end layer are cleanly separated by using Apache Kafka as a messaging layer and as a mediator between the two. The Kafka layer also serves as a gateway for external data and service used by diwo. Internally, diwo actors communicate via AKKA asynchronous messaging.
Most analytics batch and streaming, is performed using Apache Spark distributed computing engine and SparkML library. Pre-developed models can be imported into diwo using PMML standard and deployed for scoring in diwo analytics pipelines. Spark jobs are triggered and managed through AKKA actors. Raw and processed datasets are persisted primarily in Apache Cassandra whereas semantic knowledge is currently hosted in RDF format in Virtuoso.
diwo® hardware infrastructure
diwo runs on a dedicated cluster of commodity hardware with redundant storage and computing nodes to provide fault-tolerance and resiliency.
diwo requires four logical clusters one–each for AKKA, Apache Cassandra, Apache Spark, and Apache Kafka. All these logical clusters share the same hardware of anywhere from 8-12 nodes, depending on the complexity of use cases.
diwo is fine-tuned to run on a standard configuration in a dedicated environment with the “on-premise” appliance philosophy, but can operate in a cloud environment if desired.