A Day in the Life

A Day in the Life of Faith, a Programme Manager

Horizon Connect, the CRM implementation, adoption, and optimisation programme at Horizon Bank aims to deliver omnichannel personalisation by leveraging a modern CRM platform, new data, data analytics, and AI. The objective is to establish broader and deeper relationships with both consumers and MSME customers, enhancing engagement, trust, and customer lifetime value. The programme operates across three different locations in the country, requiring seamless collaboration between teams. A target operating model (TOM) has been developed, detailing the 'as is' and 'to be' states, outlining the transformation required to achieve the programme's objectives.

As the programme manager, Faith is responsible for overseeing multiple projects within the bank's CRM and omnichannel personalisation initiative. Her role is business focused, not IT, and involves ensuring strategic alignment, resolving risks, driving adoption, and maintaining compliance with data governance regulations. She relies on collaboration, project planning, and risk management tools to coordinate across various formal and informal teams and stakeholders. A typical 'day-in-her-life' looks like this.

09:00 am – Programme Stand-up meeting with Project Managers

Faith kicks off every day with a daily 30-minute virtual stand-up meeting with project managers and key workstream leads in the three locations. Using Microsoft Teams for video conferencing, messaging, and document sharing, along with Jira (a tool that helps teams plan, track, and manage agile projects) and Power BI (for real-time KPI visualisation), she reviews key dashboard metrics. These include omnichannel personalisation deployment progress, customer engagement metrics, current risks and issues, and upcoming milestones. This information is also available for all stakeholders to view on the programme's intranet portal.

Project managers provide updates. The CRM Integration Lead reports that AI-driven next best action recommendations went live in pilot two days ago in mobile banking but need adjustments for branch sales teams. The Omnichannel Delivery Manager notes that SMS-based personalised follow-ups are not triggering, and IT is investigating. The Data Governance and Compliance Team raises concerns about AI model transparency and customer data retention policies in the light of upcoming new regulations and customer research feedback.

Faith takes immediate action by asking the Omnichannel Delivery Manager to escalate the SMS issue to their IT lead as the cause is unexpected, assigns a small task force to review CRM data retention policies for GDPR compliance, and ensuring AI-generated recommendations are explainable to customers. These tasks are tracked in Jira and communicated via Teams messaging.

10:00 am – Executive Steering Committee Meeting

Faith presents a programme update to retail banking executives, including the Chief Operating Officer (COO), Chief Marketing Officer (CMO) and the Chief Digital Officer (CDO). She uses Microsoft PowerPoint for presenting programme KPIs and Confluence, a team collaborative tool, for centralised documentation that they can all access. Microsoft Teams enables real-time updates and messaging during discussions as if participants were face-to-face. The collaborative and project management tools that the team and stakeholders use are fully integrated so that information is only ever input once.

Discussions focus on initial CRM customer engagement impact, with mobile banking seeing a 20% increase due to AI-powered recommendations in two days. Noting that branch CRM adoption remains inconsistent because of some frontline staff adoption barriers that were a hangover from the legacy system that is being replaced.

Key decisions include introducing a 'human-in-the-loop' model for AI recommendations, reviewing CRM data storage policies, and launching a CRM adoption training programme. Actions are logged in Jira, with updates shared via Teams chat. A 'human-in-the-loop' model means that AI-generated insights or suggestions are reviewed, validated, or adjusted by human experts before being acted upon.

11:30 am – Data Governance and Compliance Review

Faith joins a session with the Data Governance, Compliance, and IT Security teams to ensure CRM-driven personalisation complies with new regulatory frameworks to be implemented next year. Using Jira to track governance issues, Power BI for data analysis, and Teams for real-time messaging, they discuss customer consent management, data retention policies, and AI model transparency.

Decisions include implementing a customer-facing transparency dashboard, adjusting CRM data retention policies to comply with GDPR, and conducting an AI bias audit. A customer-facing transparency dashboard for data and AI would enhance trust by showing how their data is collected, used, and protected. It would explain AI-driven decisions in credit scoring, fraud detection, and personalised offers, offering insights into fairness, accuracy, and potential biases. Customers could adjust AI preferences, control data sharing, and access real-time security alerts. The dashboard would also display performance metrics, privacy safeguards, and reasons behind AI-generated recommendations. This tool would go beyond regulatory compliance and improve customer engagement, empowering users with greater control over their financial data and AI interactions. Actions are logged in Jira, with updates shared via Teams messages.

12:30 pm – Lunch and CRM Vendor Check-in

Faith has a working lunch with the CRM vendor to discuss AI model improvements, data governance enhancements, and best practices from other banks. Vendor commitments, including delivering AI model updates within three weeks, are tracked via Jira (which allows third-party access using permissions to control what they can see and do).

2:00 pm – Programme Performance and Risk Review

Faith meets with the customer analytics team to review personalisation performance and risk management. Using Jira for tracking risks on the Risk Register (detailing identified risks, impact, likelihood, owner, mitigation plan, and status), Power BI for engagement trend analysis, and Teams for real-time discussions, she notes that customers engaging with personalised offers have a 15% higher conversion rate, email engagement remains low, and high-net-worth clients prefer direct advisor engagement over AI recommendations.

She initiates mitigation actions, including refining AI-driven segmentation and planning additional CRM adoption training for branches, the contact centre and relationship managers. These are updated in Jira and communicated via Teams messaging.

4:30 pm – End-of-day Wrap-up and Next Steps

Faith updates the programme dashboard in Confluence, sends a summary report message to executive stakeholders via Teams messaging, and aligns with IT and Compliance on CRM data governance enhancements. By 5:00 PM, she logs off, recognising that while CRM-driven personalisation is improving, stronger frontline adoption strategies, stricter data governance controls, and AI transparency enhancements are still needed.

But that's a job for another day!

Note: other software is available.