First Look: Sparkling Logic Update

Sparkling Logic is focused on enabling business and data analysts to manage automate decisions better and faster – what they call Analytics driven Decision Management. Sparkling Logic was founded in 2010 and I have blogged a few times about their decisioning platform (most recently here). Customers include Equifax, Paypal, FirstRate, Accela, Northrop Grumman and others across a wide range of solution areas with a strong focus on enterprise customers. These enterprise customers are very focused on multiple projects, enterprise integration and supporting both on-premise/cloud deployments.

The Product Portfolio now includes Pencil, a decision modeling and requirements tool, and SMARTS, their full lifecyle decision management platform supporting predictive models, data analysis, and expertise / business rules. SMARTS is available on premise, on cloud or embedded in another product and runs across Java and .NET deployments. SMARTS includes form-centric rule authoring, rule induction from data, strong navigation between the various components and integrated collaboration.

Pencil was added to the product portfolio recently to add support for decision modeling with the Decision Model and Notation (DMN) standard along with a glossary. Pencil provides graphical or Excel-based interfaces that share the same repository as SMARTS and can be used stand-alone or to generate artifacts from the decision model for use in SMARTS. This shared infrastructure means a decision model can be included in a SMARTS project. A decision model consists of DMN diagrams and a glossary, which can be shared across projects. As the decision model is built the glossary is either referenced or constructed automatically to support the model. Elements in the glossary can be categorized for management and the use of data in processing is highlighted. Computed elements can be defined as none (for casual models) or SparkL (a subset of the language used in SMARTS allowing execution). Pencil guides the business analysts in decomposing their decision according to the DMN standard, specifying inputs and outputs as he/she goes.  Each node in the diagram can be specified using a tabular layout, text or a list of rules. SparkL used in these is verified and has type-ahead access to the glossary. Models can be versioned and compared with a nice graphical comparison.

SMARTS, like Pencil, is browser-based. It continues to support a collaborative environment with fluid rule authoring that allows rules to be changed between decision tables, decision trees, decision graphs and text as necessary, combining the right mix of metaphors for each project. The ability to see how the current rules affect a set of data (in real time as the rules are edited) is still central to the product experience and data, analytics and rules are integrated with each other throughout. New features since 2013 include:

• Cascading or inherited decisions allow a decision to be extended or overridden as necessary to deliver a specific version. For instance, a decision on underwriting might be defined and then specialized for California. Rules can be added or removed and values changed. SMARTS remembers the original, allowing for detailed comparison. Multiple levels can be defied and SMARTS ensures that elements that have not been overridden can be changed and these changes are inherited.
• Native PMML support has been added and 10 PMML 4.2 model types can be executed with no-reprogramming – just bind the interface into SMARTS. This is combined with the “Blue Pen” capability to use analytic techniques like rule induction to find rules in data. Many analytic algorithms can be applied to data inside SMARTS. PMML models can be dragged and dropped into the project either as black box models (just binding the data for the model to the project) or exploded into a set of SMARTS artifacts.
• Lookup models are likewise treated as black box models that are bound to a task in a decision flow. These tables can be defined in the tool, imported from spreadsheets,or managed externally and the query is defined using the SparkL language. They can return one or many answers that are simple or complex data objects. This can all be managed in releases and captured in the tracing etc. This allows potentially very large lookup tables to be managed and versioned without having to convert them to business rules. The fully indexed table model engine guarantees fast execution.
• Built in support for champion/challenger or A/B testing means that experiments can be defined for any step in the decision. Any number of alternatives can be defined for a given step. A set of experiments can be defined for the overall decision that define which of these alternatives should be used for each of the tasks that have alternatives. Random or non-random selection criteria can be defined for allocation. Experiments can be set up to use all, none or some of these strategies in a particular simulation run or deployment. Alternatives can be defined explicitly or the Blue Pen feature can be used to use machine learning to find alternative rules in a training set. As these rules are identified they are injected into the alternative decision task approach so that they can be used in the experiment. Experiments can be run as simulations with test data or in production.
• Starting with the Quebec version, a new graphic investigation feature provides a graph of the rules fired for a specific transaction that led to a specific conclusion. This includes the data and can be used to understand the execution of a specific transaction or a group of transactions.
• SMARTS supports multiple project enterprises with extensive lifecycle management and task automation. Users can define a flow with tasks for everything from machine learning, to simulation, release management to testing. New versions of rules or models or data can be picked up and included automatically, allowing for instance a modeling team to provide new versions of models without requiring manual configuration. Projects and libraries can be imported and synchronized, deployments managed etc.

In addition, the product is localized into English, Japanese, Chinese and Spanish. For OEM customers the user interface and documentation can be branded to allow the product to be deeply integrated into a commercial offering.

More information on Sparkling Logic SMARTS can be found here and Sparkling Logic is one of the vendors in our Decision Management Systems Platform Technology Report.