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Driving improved customer and business outcomes through automating Standard Life’s BI capabilities and focusing on KPI interpretation

Challenge

Standard Life were confronted with a number of challenges that they were keen to tackle with our help. Their existing customer programme dashboard reporting was comprehensive and met a high standard, but it took too long to refresh – it was a manual weekend task. This meant that strategic business leads (product owners) did not have access to real time insights and were waiting a long time for questions to be answered. This slowed down decision making, despite there being an aspiration within customer-focused activities to test, learn, and scale. This ambition was impossible to enact given that the underlying feedback loop was not timely.

The current skilled senior analysts were pulled in multiple directions. Whilst they positively impacted a wide range of aspects of their customer activities, they didn’t have the luxury of time to review, refine, and automate their solutions. Too much analyst time was being spent on data engineering and production – not on  interpreting results  and understanding what they meant for customer outcomes. Additionally, there was a lack of consistency in KPI definitions, calculations, time frame, and data sources.

Overall, there was a keen desire within the business to move towards greater insight creation and usage of data science techniques as led by a new chief data scientist. Our challenge was to help Standard Life put the foundational, consistent building blocks in place first. This would then provide their experienced analysts time to up-skill and pivot to higher-value analytics.

 

Approach

Our approach began with working with the business leads of each team to capture objectives in order to understand the actionable insight the squads require so they can make decisions. This helps us to understand what activities are driving value and so should be scaled/rolled-out. We worked alongside the client’s senior analysts to review what data existed already and to understand potential KPI and data gaps. We then engaged the business to agree definitions, data sources, and calculations.

This work allowed us to establish the right KPIs and control group methodology to enable effective reporting. We concluded with creating a connected view of measurement within Tableau dashboards. This allowed self-serve by analysts, squad members, and business stakeholders to drill down across various levels of detail covering channel engagement, completion of customer call-to-action, and measurement of commercial impact.

“Having the Merkle team working with us has enabled us to baseline and automate our measurement and business intelligence through increased consistency of KPI definitions and greater use of our tools. This will enable my team to explore new analytical techniques as our chief data scientist leads the expansion of our data science capability.”

Ian Johnston

Head of Data and Analytics

Results

The results of our work were wide-ranging. Overall, our efforts freed up analyst time from BAU reporting with dashboards now on an automated daily refresh schedule (refreshing at 7am before colleagues start their working day). We enabled the consistent measurement of KPIs by unifying reporting across the business to create a single, actionable view of performance, allowing for direct comparison of activities and their efficacy. We introduced self-serve analytics to the business, increasing access to performance measures to wider stakeholders across a broader range of teams (e.g. digital, product, marketing, operations, etc.)

We truly empowered business decision makers with the data and insights needed to excel (improve business outcomes). We made real-time insights available to stakeholders at all levels which empowered fast paced data-driven decision making for the business. This then enables fast, iterative A/B testing, quickly improving the offering to customers, and allowing improvements to rapidly scale.

We were able to encourage greater collaboration across client teams, with the insight from the dashboards facilitating wider discussion on how to improve customer journeys. All colleagues now have greater confidence in the new automated output and significantly greater time is spent on the interpretation and discussion of next steps (Stop/Continue/Scale).

Our work led to more and more squads and business teams wanting their own dashboards to track performance.  We were able to meet the demand because we had developed an approved library of KPIs, meaning new dashboards were stood up quickly. Our approach set the client’s data and analytics team up for greater people development, moving the capability away from simple data engineering and reporting to greater use of data science and predictive analytics. This has driven a step change in the use of data within the client’s business, ultimately creating better outcomes for customers. 

We expect the number of self-serve dashboard users to reach 100 during the first half of 2022 given the roll-out of further programme squads, recruitment of additional data scientists and further adoption of agile ways-of-working.  This would represent a 4-fold increase on current levels of usage, illustrating that these dashboards are playing a crucial role in the adoption of self-serve analytics across the business. 

15

min run time for individual dashboard  production (reduced from 7 hours)

30

KPIs established across channel engagement, completion of customer call-to-actions and measurement of commercial impact

27

colleagues are using the dashboards with 19% of users accessing all available dashboards

Keys to success

  • Close client collaboration to ensure KPIs were in line with the business objectives
  • Delivery of KPIs with clear actionability
  • Self-service successfully promoted by engaging client teams in our development of the Tableau dashboards to build trust
  • Full transparency within the dashboards, with clear business definitions, data sources and calculations provided

Discover how we did it. Contact us today.

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