CASE 1. Wealth Management Platform
Effective access to data analysis and reporting
Wealth Management Platform providers operate in a competitive environment where margins are thin, and their customers are price sensitive. Accurate management information and insights are critical to managing and growing an organisation.
We were approached by a major UK wealth platform provider who had rapidly expanded their business, primarily through a series of acquisitions and mergers. This led to information being stored on multiple systems, each holding their own individual management reports and commercial data.
The rapid company expansion meant that accessing vital information was a time-consuming and difficult process. Failing to do so in a timely and straightforward manner could be hugely financially detrimental, both to the company and its clients’ portfolios.
They lacked the resources and in-house technical expertise to solve the problem within the timeframes they had set themselves and were in danger of losing their competitive edge.
To create a simplified platform that could pull key data together from the various sources and provide effective analytical tools.
We began by installing business analysts to determine how the data sets were linked, and what approach would be needed to establish the required resources.
A consultative approach meant that we could work directly with C-level to identify further opportunities for improvement, and to benefit from a clear line of communication.
We then detailed and provided the resources needed to successfully complete the task, including data analysts, dev ops and a lead project manager. We defined the costs upfront, and proposed lead times in line with their completion targets.
The organisation could access key data virtually at the press of a button, including:
• Identifying the profitability of the most important customers
• Time lag between various sales activities and any activity leading to increased revenues
• Identifying customers that are likely to increase or decrease their business in the following year and identifying the triggers that can predict customer churn
• Remained competitive and were able to continue their expansion programme
• Had a system which was more conducive to effectively integrating new acquisitions
If you need a Rockstar to help you take control of your data and remain competitive, speak with a consultant today.
CASE 2. Ana Credit - Resourcing complex banking regulatory challenges
Harmonising data on an international level
Since 2014 the European Central Bank (ECB) has required all banks within the EU to provide analytical credit datasets- ‘Ana Credit’- detailing all individual bank loans and harmonising them across all member states.
We were contacted by an international bank who were looking to hire long-term data engineering and analytics teams. They were working towards building a data quality framework using real time, automation, and front-end capabilities to meet regulatory requirements and reduce the overall future capacity.
Establishing which critical data sources were required by the regulatory authorities presented the first challenge.
A secondary problem was that these data sources were owned by various teams which all had individual systems, governance practices and access rights. This meant that teams struggled to understand and maintain all the data within their remit.
Not solving these challenges meant the bank were at risk of substantial monetary fines from the regulatory authorities.
To build a data quality solution which could serve the business and regulatory processes. To create a data quality solution and framework which provided checks and insights into the company’s data assets to provide a monitoring overview of the health of the company’s data.
We started by setting up a team of analysts to investigate which teams and data assets were in scope. The team discovered what necessary data quality rules and checks were needed to not only meet regulatory requirements, but also to serve the business.
We worked directly with their C-level to provide clear timelines, budget requirements and expectations for project delivery.
Analytics skillsets were required to identify the necessary checks that needed creating by the engineering tech teams.
We then evolved the project team from a small number of analysts, to an experienced cross functional data engineering team working in a data bricks environment using SCRUM and Lean Six Sigma techniques, delivering over 70,000 data quality checks and insights to the ECB.
Front-end visualisations were developed to allow analytics teams real time monitoring of data quality checks.
All ECB regulatory deadlines and requirements were met:
• Improved overall data quality within the clients’ systems
• Automated pipelines were set up to keep a constant overview of the health of all KPI
• Bridged the data gap between finance, risk, and management
• Real time monitoring of pipelines
If you have a similar resourcing challenge, or would like to explore how we can help in your digital transformation, speak with a consultant today.
CASE 3. Decision-making and forecasting
Optimising price decision-making and forecasting
E-commerce is an ever-evolving space where pricing, and price strategy can make or break a product’s online success. In order to stay ahead and continually grow sales, e-commerce businesses must embrace their technological challenges and create systems that exploit one of their most valuable assets - their data.
We were approached by a large UK-based eCommerce retailer who sold a varied range of electronic, domestic and consumer goods at highly competitive prices. Part of their shorter-term vision was to become more sophisticated in the way they used their data, and to plug any holes in their technical capability.
Increased competition, lack of technical ability, and the onset of high inflation, meant that optimal pricing was becoming harder to determine. Without the right strategy and deployment of expert resources, the client was becoming vulnerable to losing market share.
To create a global price management tool that used price elasticity to identify optimal pricing and conversion strategies.
To understand optimal price points for its products and how that would affect overall demand and conversion within their e-com space.
We installed and managed a cross functional tech team to build machine learning models and understand the price sensitivity around the client’s products.
Using a system of strategic workshops, we developed a model strategy which resulted in an ‘unconstrained’ econometric panel model, supported by various pricing mechanisms, built in a PySpark framework.
Our team of Rockstars used historical analysis of demand, macroeconomic trends, and personalisation metrics to identify price sensitivity in relation to demand.
Multiple pricing engines were developed to produce optimal price recommendations and net sales forecast. Analysis of the seasonal calendars were key, whilst focussing on key datasets such as transactional, price history and clickstream.
Incremental net sales and standard margin uplifts of over 30M in first full year after implementing the PMS system:
• Increased decision-making allowing responsiveness to changes in business environment
• Automated, hourly pipelines were set up to keep a constant view of all overall KPI health
• Increased transparency on cost of sale allowed for direct pricing strategies to fuel business objectives
If you have a similar goal that requires a team of Rockstars to see it to fruition, speak with a consultant today