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Automation Delivery Models​

Paving the Path to Hyper-Automation

Digital Transformation – beyond buzz-words

Nowadays, any IT concept that generates value and has traction in the market becomes so over-used in publications and speeches that it gradually loses its true meaning and becomes a cliche.

Digital Transformation is no exception. We can barely see through the buzzwords and get the true understanding of how this type of service helps organizations get the most out of their resources and streamline their processes.’s approach to Digital Transformation aims to cut through the clutter and get to the roots of our customers’ real needs and pains first.

We pin-point real problems and focus our solution design and architecture capabilities to improve the way our customer’s business works whilst keeping their business running throughout the process.

Simply put, #Digital Transformation implies the intertwinement of two fundamental activities:

  1. #Digitalization of non-digital processes (e.g. switching from paper to paperless);
  2. #Process Automation – plagued by another buzzword – RPA -, which is in fact a much wider topic.

Every process improvement iteration is done through a set of predefined steps:

  1. Situation Analysis – Identify what doesn’t work right or efficiently enough;
  2. Process Analysis – Define how things should work to maximize the business outcome;
  3. Solution Design – Define the most appropriate technical solution that gets closest to the ideal scenario;
  4. Solution Development – Lean development of the technical solution. This is where #Digitalization and #RPA falls into place;
  5. Deploy and Piloting – Run the business activities on both the old and the new process. Adjust and tune the new one to ensure business reliability and performance;
  6. Process Switch – Switch to the new process and keep the old one as backup;
  7. Metrics & Measurements – Get all the relevant data from both technical and business perspective while running the business activities on the new process;
  8. Data Analysis and Statistics – #AI-driven data analytics;
  9. Optimizations – Get a clear idea of how the solution can be optimized and be better adapted to real business needs;


Have a look on how all these add up and shape a methodical approach of what calls #Digital Transformation.

It may sound long and daunting, but we do it fast and precise while keeping each step documented for future analysis.
Changing nuts and bolts on a running engine is not a walk in the park, but our team of trialed and tested technical consultants are here to get this done.

Situation Analysis​

Identify the Business Outcome of the Current Mode of Operation and compare this with the Business KPIs

Identify and extract the business context and the delivery context as perceived by the customer. Identify and map the current execution process as perceived by the customer

Identify all costs (time and money) of the Current Mode of Operation – both CapEx & OpEx

Process Analysis

Observe the Current Mode of Operation, take notes and extract the execution process.

Extract business, technical, operational, commercial , regulations and other constraints and limitations

Extract all non-IT activities. Activities that involve manual repeatable work (ex: hand signatures, paper scanning, etc)

Together with the Customer define an altered version of the Desired Mode of Operation – the ideal execution process.

Map how all constraints and limitations impact the implementation of the ideal desired process

Define the Future Mode of Operation: How the execution process will look like, what non-IT activities will be digitized and how all these changes will impact BAU (business as usual)

Gap analysis between Current Mode of Operation and the ideal process (Desired Mode of Operation)

Define an execution process that can actually be implemented taking into consideration the unavoidable constraints and limitations

Solution Analysis

Check the Key Success Factors against Business KPIs and Desired Outcome.

Define the technical solution for integrating existing/new 3rd party IT tools.

Define solutions to overcome automation failure: back-ups, roll-backs, return to current process, etc

Non-functions Req: Performance, Security, User Experience, Ease of use, Ergonomy

Define the technical solution to digitize(part of) non-IT activities.

Define the quality parameters of the solution, the quality assurance and the quality control process for the automated solution. As well as how to measure against thresholds.

Define the Data that the Automated process must generate and how this data is aquisitioned

Define Key Success Factors of the Solution – what are the most relevant aspects the solution must solve to be considered a success

Define the technical solution to automate the newly defined execution process.

Define the variable aspects of the automation and how they can be adjusted to tune the automated process.

Solution Development

Deploy technical solutions for quality control, risk assessment, risk mitigation, compliance and conformity.

Scrum/Scrumban, Kanban or Lean Iterratice Development

Chose development tools, technologies, techniques, development frameworks, programming patterns. Actual implementation of the architecture framework. Define guidelines and practices, development process and procedures.

Deploy DevOps infrastrusture for continuous integration and delivery. Automate builds and build smoke tests.

Define sprint backlog for maximum relevance for the business through low hanging fruits.
Particular iterations must be ready for pilot deployment with immediate effect on business operations.

Integrate quality control automation into the DevOps infrastructure: unit tests, UI test automation, logs analytics, build health check, etc.

Solution Deployment

The business starts to operate based exclusively on the new solution.

Make sure the failover mechanism are in place and triggered on failure markers. Define procedures for roll-back to current mode of operation in case of solution downtime.

Prepare the guidelines for the future mode operations and adjust the operating parameters

Final stage before switching to future mode of operation. Last checks on quality, compliance and conformity. Final adjustments and preparations are made.

Make sure the data from all types of logs are relevant for the production environment. Make sure all business operations steps are covered by logs data.

Start the preparation of all technical aspects for the future mode of operations: software tools, hardware, hardware integrations

Define training materials and knowledge assessments. Make sure the personnel is prepared for the future mode of operation.

Start the future mode of operation in a contained and carefuly observed context whilst preserving the current mode of operation as backup.

Automatic deployment on staging for user testing purposes. Preserve common mode of operation but test the fitness of purpose for each iterration


Compare the performance indicators of the new mode of operation with the desired business outcomes (measured as KPIs). Does the new mode of ops lead to the desired business outcome?

Measure tehnical operations params against predefined thresholds. Link this to solutions quality parameters

Measure if the operating params of the automated solution are according to the solution key success factors.

Measure the costs and effort of the new mode of operations. Check against previous costs, efforts, delays, inneficiences.

Identify which are the most common points of failure and how likely a failure can happen. Also measure the failure rate as well as all other non-functional requirements.

Identify which are the most relevant KPIs of the process execution according to the business KPIs and solution’s key success factors.

Compare the performance indicators of the new mode of operation with the desired business outcomes (measured as KPIs). Does the new mode of ops lead to the desiredbusiness outcome?

Measure the efficiency of all the integrations (hw and sw). Measure how the digitized activities influence the overall efficiency in comparison with the manual ones.

Data Analytics & Reporting

Define analysis dimensions together with the stakeholders. Define OLAP cubes and prepare the ETL (extrat transform & load) functions to get the data into the desired analysis framework.

Define how and when the data should be reported to make the most sense for the stakeholders.

Define what are the most relevant correlations that should be monitored. Define what statistics correctly map the business KPIs. Consultancy from Data Scientists will be used.

Define custom neural network for smart statistics and correlations. Both supervised and unsupervised learning should be used.


Assess the impact of all approved changes on the current automation level. Assess feasibility

Extract optimization options for all non-functional requirements of the automation solution

Extract options for data gathering performance and security optimizations.

Anlyze and extract meaningful conclusions on the statistics deviations of both process execution and business KPIs.

Extract options for data gathering performance and security optimizations.

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