Information Management and Governance, Uncategorized

Innovation and Data

Data Explosion:

As a benefit of advances in technology, the volume and availability of data is increasing exponentially, including the ability to collect rich data as collateral from operational transactions.

Sensors permit the increased gathering of data, some of which can be procured commercially – performance data from jet engines, weather data around seasonal storms, wrist band data from families visiting amusement parks, patient data from medical devices, etc.

Key Advances – enabling data innovation:

Advances in algorithms enable more sophisticated analysis of data – intelligent automation, cognitive –  creating the ability for automation to become more seamlessly integrated into the user experience. Most – if not all – are hugely dependent on the quality and availability of data.

Advances in cloud platforms enable the analysis of larger volumes of data, more opportunistically with on-demand, cost-effective scaling.

Within organizations, data can be classified into the following:

  1. Marketable data– data-oriented products or services that have market value, whether in raw or refined/aggregated form
  2. Management data– KPI information gathered from business systems, used to inform decision makers
  3. Transactional data– information generated from an organizations business activities, whether banking transactions, audits, sales activities or IoT logs
  4. Operational data– Presentations, R&D activities, thought pieces, brochures, client data processed by employees

Opportunities for Innovations:

The evolving discipline of data science is imagining new, innovative and creative ways to combine data, extract “signals” and drive value – whether its from anticipating possible outcomes (mortgage defaults as a function of weather patterns and number of computers), identifying lost revenue (hospital networks providing costly diagnostic services, but losing higher margin treatment revenue), or identifying interesting correlations (consumer buying patterns following summer storms)

Each of the above classifications of data present opportunities for innovation:

  1. Marketable data is the holy grail: with appropriate governance, harvesting and deriving revenue from data available as collateral from business.  Innovation drives things such as, how can the data be refined or enriched to increase value to licensor?  How must it be anonymized to meet regulatory requirements?  How to achieve fair share of downstream revenue?
  2. Enriching management reporting and optimize processes by introducing additional data e.g. road construction plans influencing product delivery routes or performance of local sports teams affecting snack sales;
  3. Transactions can be mined to optimize performance, contribute to regulatory or management reporting and can be refined with robotics and intelligent automation
  4. Operational data can be cataloged, leveraged – avoiding re-creation – and tracked for compliance with regulations or client expectations, or disposal

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