Ada Robotech's Implementation Steps

Ada Robotech divides the implementation into three practical steps as illustrated below.

Step 1: Implementing Customer Experience Management

The first step in Ada Robotech's implementation process focuses on Customer Experience Management. The primary focus areas in this step are marketing, sales, and support. The purpose of this step is to enhance the overall engagement and interaction of the customers with your business. By implementing this software component, Ada Robotech aims to provide its customers with a better understanding of their own customer's journey, behaviors, and needs. 

The outcome of this step includes the generation of data and analytics regarding various aspects such as Leads, Opportunities, Incidents, Satisfaction, and Customer Value. This data is extremely useful in identifying bottlenecks, understanding customer preferences and improving the overall customer experience.

Step 2: Implementing Integration and Automation

The second step in the implementation process is the implementation of Integration and Automation. This step is primarily focused on integrating the customer's data from other systems which could be anything from ERP (Enterprise Resource Planning) systems, Supply Chain, POS (Point of Sale), to Unstructured Documents. 

The main goal here is to centralize and synchronize all pertinent data to ensure smooth and efficient business operations. This streamlined integration and automation process allows for better data management and reduces the risk of errors that can occur due to manual data entry or transfer.

The outcome of this step includes data and analytics concerning Orders, Products, Logistics, Finance, Documents, Images. This data is valuable for businesses to track their operations, manage their resources better and make more informed strategic decisions.

Step 3: Implementing Artificial Intelligence

This step focuses on the implementation of Artificial Intelligence (AI). This primarily involves harnessing the power of machine learning to learn from data obtained from the previous steps.

Machine learning is a branch of AI that involves teaching computers to learn from data and make decisions or predictions based on that data. In this context, the machine learning algorithms will analyse the data collected in steps 1 and 2. This analysis will allow the AI to understand patterns, correlations and anomalies within the dataset.

Following this analysis, the AI will use this understanding to provide insightful information to business stakeholders. This is a critical step as it allows the AI to transform raw data into actionable insights. These insights can then be used to inform business strategy and decision-making.

The outcome of this step includes data and analytics that provide a number of suggestions. These can range from cross-selling or up-selling opportunities, to predictions about customer behaviour. This information can be vital for businesses looking to optimise their sales strategies and improve customer engagement.

Finally, the AI can also contribute to the generation of a knowledge-base. This is a centralised repository of information that can be used for various purposes within the business. This could include staff training, customer support, or further data analysis.

In summary, step 3 involves using AI and machine learning to analyse data and provide insightful information to business stakeholders. This information can be used to optimise business strategies and contribute to the creation of a valuable knowledge-base.