Over the past few years, we have seen tremendous advances in machine learning (ML) and artificial intelligence (AI). Rooted in these inspiring technologies is the idea of robotic process automation (RPA), the possibility of automating routine and mundane tasks with software robots capable of interacting with traditional software systems in the same way as human operators would & replicate, enhance their knowledge.

Enterprise executives are attracted by the numerous benefits of RPA, which include significant cost savings and productivity improvements, but they are often left wondering how to best adopt these technologies to drive long-term growth.

At SARCI, we introduce a simple 3-step adoption model for creating an automation-centric enterprise, where both mundane & intelligent automation spans across physical infrastructure, business management software, operations management, analytics as visualized below. When an enterprise successfully reaches the last step of our model, the enterprise is ready to transition into a more agile-systemic, data-oriented model of operation and fully reap all the benefits of RPA, AI, ML.

The Three Process Layers

Records - source of all data

Records are continuously created, exchanged & updated within a business.

Challenges arise when either the record itself is not captured digitally in a reliable manner or if siloes keep these information in ways that are not inter-linked with each other.

Losses due to delayed or incorrect capture of data and failure to inter-link with corporate controls cannot be overstated.

This the first layer of automation.

Knowledge - what helps to run the business

The knowledge workers of a business pull data from different sources & apply their knowledge on it to derive meaningful summary.

Examples include excel sheets for purchasing plans, calculating sales profit, reconciliation spread-sheets, audit of tax+payables etc.

Studies show more than 50% is usually repetitive work with little value-add.

The second layer of automation.


Analysis - a guide to improve the business

Data is only growing & the efforts to manage it grows even more exponentially. Bring into the mix, the multiple process dependencies and what we have is burnout & errors.

Much time however is spent in the collation of data & getting to the trends rather than taking the steps to improve.

End result is that there is not much time to actually make the adjustment.

The third layer of automation.

Automation Solutions

Transactional Automation

Mini-ERP systems with configured industry standard rules for governance, budgetary control, procurement process, sales & client service, financeĀ  and other standard functions ensure a strong foundation.

Extended features for automated handling of paper/email/excel/web data & linkage to various process, ensure that the records are kept in a consistent manner for further processing.


Work Intelligence Automation

Capture work knowledge formally in a way that can be replayed independent of the person.

Work Bots are configured to validate & collate using standard & custom rules for due diligence, planning & forecast, client service, finance and other standard functions ensure a strong foundation.

The Work Bots are optionally used in a supervised manner to exchange data between themselves to mimic actual workflows.


Cognitive Automation

Correlate data gathered from multiple sources to provide one consistent status view with comparative predictive models.

Template-based solutions help internal teams meet the demand for rapid results.

Focus on exception analysis, creeping deadlines and lateral effects on core business needs like cash-flow to help bring focus quickly to key impact areas.


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