[vc_row css_animation=”” row_type=”row” use_row_as_full_screen_section=”no” type=”full_width” angled_section=”no” text_align=”left” background_image_as_pattern=”without_pattern”][vc_column][vc_text_separator title=”1. Complex Data” border=”no”][/vc_column][/vc_row][vc_row css_animation=”” row_type=”row” use_row_as_full_screen_section=”no” type=”full_width” angled_section=”no” text_align=”left” background_image_as_pattern=”without_pattern” css=”.vc_custom_1567586058967{padding-top: 20px !important;padding-bottom: 20px !important;background-color: #e8e8e8 !important;}” z_index=””][vc_column width=”1/4″][vc_column_text]

Operations

[/vc_column_text][qode_accordion style=”toggle”][qode_accordion_tab title=”Network Management” el_id=”Network Management”][vc_column_text]ML used to manipulate large data sets, diagnose issues, predict and prescript actions. There is a mixture of more “traditional” activities such as network monitoring and capacity management which will become part of the closed loop of SDN/NFV (self-configuration, self-optimizing and self-healing).[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Revenue Management” el_id=”Revenue Management”][vc_column_text]ML used in revenue assurance exercises, the prediction of issues in bill payment processing and collections, and customer debt collection.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Assurance” el_id=”Assurance”][vc_column_text]ML used to manage large data sets, diagnose issues, predict future issues and prescribe solutions.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Fraud/Security” el_id=”Fraud/Security”][vc_column_text]Use of ML to undertake pattern and anomaly detection in both fraud and security use cases.[/vc_column_text][/qode_accordion_tab][/qode_accordion][/vc_column][vc_column width=”1/4″][vc_column_text]

Channels

[/vc_column_text][qode_accordion style=”toggle”][qode_accordion_tab title=”Issue Resolution” el_id=”Issue Resolution”][vc_column_text]Identification of issues and diagnostic routines on large data sets (often from network) to help agents better understand a customer issue and provide resolution.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Customer Experience Management” el_id=”Customer Experience Management”][vc_column_text]Use of ML to manage data and find patterns, anomalies and segmentations. Including text, speech analysis and other perceptual classification techniques. Used in various ways including voice of the customer and customer journey mapping.[/vc_column_text][/qode_accordion_tab][/qode_accordion][/vc_column][vc_column width=”1/4″][vc_column_text]

Marketing and Sales

[/vc_column_text][qode_accordion style=”toggle”][qode_accordion_tab title=”Customer and Market Understanding” el_id=”Customer and Market Understanding”][vc_column_text]Use of ML to find patterns, anomalies and segmentations. Including text, speech analysis and other perceptual classification techniques. Used in various ways within marketing – including segmentation, background understanding for marketing team and reacting to trends.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Brand and Media Management” el_id=”Brand and Media Management”][vc_column_text]Use of ML to find insight in structured and unstructured data from across the internet for tasks such as monitoring brand reputation.[/vc_column_text][/qode_accordion_tab][/qode_accordion][/vc_column][vc_column width=”1/4″][vc_column_text]

Other Functions

[/vc_column_text][/vc_column][/vc_row][vc_row css_animation=”” row_type=”row” use_row_as_full_screen_section=”no” type=”full_width” angled_section=”no” text_align=”left” background_image_as_pattern=”without_pattern”][vc_column][vc_text_separator title=”2. Processes” border=”no”][/vc_column][/vc_row][vc_row css_animation=”” row_type=”row” use_row_as_full_screen_section=”no” type=”full_width” angled_section=”no” text_align=”left” background_image_as_pattern=”without_pattern” css=”.vc_custom_1567586058967{padding-top: 20px !important;padding-bottom: 20px !important;background-color: #e8e8e8 !important;}” z_index=””][vc_column width=”1/4″][vc_column_text]

Operations

[/vc_column_text][qode_accordion style=”toggle”][qode_accordion_tab title=”Trouble Ticketing” el_id=”Trouble Ticketing”][vc_column_text]Intelligent automation used to automatically raise tickets, improve the routing of each ticket and find areas for process improvement.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Order Management” el_id=”Order Management”][vc_column_text]RPA and more intelligent automations to create, check and provision orders.  ML used to prescribe resolutions to orders that are flagged as having issues.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Incident Management” el_id=”Incident Management”][vc_column_text]Categorization of the high volume of alarms generated by the telco network to identify those which are critical; plus predictive capabilities to identify best resolution to each alarm.[/vc_column_text][/qode_accordion_tab][/qode_accordion][/vc_column][vc_column width=”1/4″][vc_column_text]

Channels

[/vc_column_text][qode_accordion style=”toggle”][qode_accordion_tab title=”Case Management” el_id=”Case Management”][vc_column_text]Automation of process flows around customer cases generated in the contact centre or cross-channel.  Processes reach across to other departments such as the creation of tickets field services.[/vc_column_text][/qode_accordion_tab][/qode_accordion][/vc_column][vc_column width=”1/4″][vc_column_text]

Marketing and Sales

[/vc_column_text][qode_accordion style=”toggle”][qode_accordion_tab title=”Contract Management” el_id=”Contract Management”][vc_column_text]ML, optical character recognition and RPA used to create a single repository of searchable documents, to extract or index data, create searches and analyse across the repository.[/vc_column_text][/qode_accordion_tab][/qode_accordion][/vc_column][vc_column width=”1/4″][vc_column_text]

Other Functions

[/vc_column_text][qode_accordion style=”toggle”][qode_accordion_tab title=”Supply Chain” el_id=”Supply Chain”][vc_column_text]Inclusion of automation within the procure-to-pay and sourcing processes.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Finance” el_id=”Finance”][vc_column_text]Addition of ML, optical character recognition and RPA in a range of routine activities – for example, accounts receivable or expense management.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”IT” el_id=”IT”][vc_column_text]Use of RPA and employee chatbots in processes such as user support and services.  ML used in orchestration and problem management.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”HR” el_id=”HR”][vc_column_text]Use of RPA in processes such as onboarding, ML for creation of job descriptions and ML in planning and optimization tools.[/vc_column_text][/qode_accordion_tab][/qode_accordion][/vc_column][/vc_row][vc_row css_animation=”” row_type=”row” use_row_as_full_screen_section=”no” type=”full_width” angled_section=”no” text_align=”left” background_image_as_pattern=”without_pattern”][vc_column][vc_text_separator title=”3. Personalisation” border=”no”][/vc_column][/vc_row][vc_row css_animation=”” row_type=”row” use_row_as_full_screen_section=”no” type=”full_width” angled_section=”no” text_align=”left” background_image_as_pattern=”without_pattern” css=”.vc_custom_1567586058967{padding-top: 20px !important;padding-bottom: 20px !important;background-color: #e8e8e8 !important;}” z_index=””][vc_column width=”1/4″][vc_column_text]

Operations

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Channels

[/vc_column_text][qode_accordion style=”toggle”][qode_accordion_tab title=”Assisted Care” el_id=”Assisted Care”][vc_column_text]Some limited use of ML when agents are assist customers. For example, optical character recognition and text analysis in managing email communications.  Or sentiment analysis to automatically tag posts on social media with predicted intent.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Contact Centre Infra” el_id=”Contact Centre Infra”][vc_column_text]Used particular in IVR containment where speech analytics understands intent and then prediction/prescribes routing and messages.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Unassisted Care” el_id=”Unassisted Care”][vc_column_text]ML to personalize content on website and other digital channels – also provision of next best action for the customer[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Troubleshooting” el_id=”Troubleshooting”][vc_column_text]Tools for customer or agent (assisting the customer).  May be installed on the customer device or in the OSS.  Offer diagnostics, guided and proactive fixes. Mostly using rules-based analytics today but some use of ML to understand potential future customer issues and prescriptive, proactive resolution.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Digital Commerce” el_id=”Digital Commerce”][vc_column_text]Text[/vc_column_text][/qode_accordion_tab][/qode_accordion][/vc_column][vc_column width=”1/4″][vc_column_text]

Marketing and Sales

[/vc_column_text][qode_accordion style=”toggle”][qode_accordion_tab title=”Marketing Programs” el_id=”Marketing Programs”][vc_column_text]ML to manage data, create segmentation and prescribe next actions in programs such as churn management, loyalty and social marketing.  Also the creation of outbound campaigns via SMS and other channels.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Content and Knowledge Management ” el_id=”Content and Knowledge Management “][vc_column_text]ML used in a variety of customer-facing systems (e.g. care, marketing, retail and sales teams).  It manages the customer data in order to understand need and can also be used recommend the best content for an interaction.  AI needed to manage unstructured data = for example,  assembling the best permutations of imagery and text for a sales interaction.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Sales and Care Training and Coaching” el_id=”Sales and Care Training and Coaching”][vc_column_text]ML used to suggest learning topics and material, to design new content and understand emotion/sentiment of those being trained and coached.[/vc_column_text][/qode_accordion_tab][qode_accordion_tab title=”Owned Channels” el_id=”Owned Channels”][vc_column_text]Text[/vc_column_text][/qode_accordion_tab][/qode_accordion][/vc_column][vc_column width=”1/4″][vc_column_text]

Other Functions

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