Adventures in the Real Time Enterprise

WIKIPEDIA defines the Real Time Enterprise as

a concept in business systems design focused on ensuring organisational responsiveness that was popularised in the first decade of the 21st century. It is also referred to as on-demand enterprise. Such an enterprise must be able to fulfil orders as soon as they are needed.

Though not particularly well defined, generally accepted goals of a Real Time Enterprise include:

  • Reduced response times for partners and customers
  • Increased transparency, for example sharing or reporting information across an enterprise instead of keeping it within individual departments
  • Increased automation, including communications, accounting, supply chains and reporting
  • Increased competitiveness
  • Reduced costs

Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data

Characteristics of Real Time Enterprises

Real Time Enterprise

Figure 1: Forces and Trends affecting Redefined Real Time Enterprises

A Dated Definition of Real Time Enterprises

The Wikipedia definition of Real Time Enterprises is dated, and given the trends and forces depicted in Figure 1, not least due to Social Enterprise, Big Data and explosion of new information sources.

I redefine Real Time Enterprise as:

A business system design focused on organisational responsiveness and agility based on:

  • Holistic Information Strategy
  • Real-time analytics
  • Multi-channel Knowledge Management
  • Social Enterprise

The Social Web of Web 2.0 spawned the Social Enterprise (Enterprise 2.0). Real-time search and the immediacy of micro-blogging is driving the web in interesting directions and these forces will have a significant impact on the Enterprise.

To be a Real Time Enterprise according to my redefinition it will be necessary to tackle some endemic information management problems and ‘gear up’ for the new frontier of a Real Time Enterprise 2.5.

Storm Applied: Strategies for real-time event processing

Real Time Enterprise: 20 Common Problems

Some or all of the following exist (in varying degrees) in typical organisations:

  1. Proliferation of information systems and information system types (personal, corporate, structured, unstructured)
  2. Disconnection of information systems
  3. Limited content management lifecycle (or little rigour in its application)
  4. Limited rigour in content taxonomy, tagging, meta-data
  5. Poor search capabilities
  6. Search is silo based (no enterprise search)
  7. Limited or no social ranking capability or social search across information sources
  8. Often no assigned knowledge champions per knowledge domain
  9. Limited ‘information harvesting’
  10. Issues with provenance of information (how good is it, who rated it, when, is the rating still valid)
  11. Little or no archiving
  12. Limited categorisation of content e.g. “health warning” “gold standard” “exemplar”
  13. Content sits in wikis, ideation systems, Content Management Systems, Intranets, CRM systems, email systems and personal archives, ERP systems and Shadow IT Systems etc. Visibility of content across silos is usually poor
  14. Email is a shadow content management system
  15. Little or no strategy for use / cross-population of external knowledge with internal (e.g. research, public data sets, pattern seeking.)
  16. Limited information governance processes, use of knowledge management systems ‘culturally optional’
  17. No single sign on across platforms
  18. No clearly defined ‘knowledge portal’
  19. Multiple copies of same content exist
  20. No capitalisation on ‘Real Time Enterprise’ pattern

These 20 problems are serious barriers to achieving the goals I define above for a true Real Time Enterprise.

Advanced Analytics with Spark: Patterns for Learning from Data at Scale

20 Real Time Enterprise Solutions

20 solution areas to consider for Real Time Enterprises:

  • Define Information Strategy
    • Define ‘content harvesting’ strategy, process, ownership, metrics and KPIs (should be sub-part of overall Information Strategy)
    • Define security strategy as part of Information Strategy
    • Define Content Taxonomy as part of Information Strategy
    • Define strategy for use / exploitation of external content (Pattern Based Strategy)
  • Define and enforce mandatory content management lifecycle
  • Implement Enterprise Search as a ‘quick win’
  • Define knowledge domains and appoint knowledge champions and custodians in each domain
  • Define metrics and KPIs – how we will success be measured?
  • Add lifecycle process training to induction and e-Learning collateral
  • Create ‘clean zone’ in the Content Management Systems where only gold standard content is added, with appropriate meta data and tagging (i.e. spring clean the ECMS)
  • Sink / archive old content (delegate to knowledge champions in each domain). Rather than attempt to fix all content, prioritise the high value content and allow the rest to ‘sink’ organically
  • Block search results from archived content or add to ‘supplementary index’ as Google does
  • Ensure searching function ranks ‘clean zone’ results highest
  • As part of content lifecycle for business documents, add rating functionality. This helps establish ‘provenance of information’
  • Create single knowledge portal with enterprise search abstracting out complexity of silos
  • Define usage patterns – e.g. if A is taken from system x and B from system y, if a composite of A+B is created where is it stored?
  • Create multi-media libraries (clipart, logos, video, diagrams, templates), and harvest content from existing information sources to populate
  • Localise search – i.e. Country / service line content ranks highest (arguable, but a likely solution)
  • Define rationalisation plan for existing content systems (consolidation)
  • Create an ‘unload your laptop’ on-ramp, although this presents challenges in terms of triage and determination of information value
  • Add Knowledge Management metrics to balanced scorecards
  • Evaluate Big Data as part of the overall information management strategy (the Real Time Enterprise will need significant computing power to exploit the full range of internal and external data sources)
  • Ensure there is a strategy and capability in place to enable agile reaction to new ‘Real Time’ detection opportunities

Real-Time Big Data Analytics

Real Time Enterprises – Challenges and Benefits

Figure 2 details some of the typical complexity in information management. The successful Real Time Enterprise will:

  • Use Enterprise Architecture as a technique to define ‘as is’ and ‘target state’ vision
  • Tackle the legacy and ‘fragmentation problems’ described above
  • Implement Social Enterprise functionality to ensure end-users are fully participating in evaluation and ranking of information (pattern and opportunity detection need not be solely delegated to automated processes)
  • Implement an holistic information management strategy
  • Leverage Big Data as part of the scalability / computational challenges
  • Implement new dashboards and analytics tools, e.g. internal Social Network Analysis tools, internal micro-blogging analytics.

Real Time Enterprise Challenges

Figure 2 – Real Time Enterprise Challenges

 

The benefits of redefining Real Time Enterprise and tackling these challenges include:

  • Deep level of understanding of information and its value
  • Improved internal and external collaboration and innovation
  • Ability to use external data sets and enrich decision making
  • Massively improved agility

A true Real Time Enterprise will be equipped to react to internal and external forces as they emerge, and capitalise on information, right from its point of creation, irrespective of its source.

Further Reading on Business and IT Strategy