Intelligent Systems

The software industry is going through dramatic changes and traditional enterprises are not immune to this transformation. For most traditional industries software based services are less than 5% of overall gross revenues. As processes become more automated and machine controls become increasingly digitized enterprises are faced with vast quantities of data. Even most software companies have yet to fully explore their data play, leaving money on the table. Data is increasingly the new currency.

Traditional enterprises will continue to improve core processes, develop new materials, engineer more efficient machines, research new fuels, etc., but as consumers and as business customers, we increasingly expect even traditional products and services to come with applications that are facilitative, collaborative, analytic, predictive and even prescriptive, in order for us to be able to maximize the return on our investments. Intelligent systems enable data to flow across an enterprise infrastructure, spanning the devices where valuable data is gathered, to back end systems where that data can be translated into insights and action.

The first step is to structure, collect and display data in static reporting format. The design of the data architecture needs recognize that this is only a minimum viable offering and that the design must support additional data streams, data merges, benchmarking and analytics. As the amount of data stored increases the architecture must allow for this with minimum degradation in quality of service.

No system exists in a silo, but rather as a component of an ecosystem of solutions and services. Integration with possible value adding third party data streams or overlays should be considered. Examples of overlays are geological, geospatial, socioeconomic, etc. Value adding data streams can be threat data, macro-/microeconomic data, ERP/CRM data, social feeds, weather data, etc. Layering data or merging data increases the value of our core data set generating a wider range of insights. To fully monetize our core data enterprises should also consider if other parties within the ecosystem could use the data to generate value.

In addition to adding depth to services, enterprises can also add breadth. Value chain integration, expansion to adjacent markets and addressing external stakeholders (such as communities, local governments, etc.) can increase breadth of the addressable population. Each stakeholder persona has their own needs and motivations that add complexity to the services being offered and marketing messaging.

Software based ‘overlay’ services to traditional core products and services can increase utilization, satisfaction and loyalty.

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