City Plumbing is a Northampton-headquartered plumbing and heating company, forming part of the Travis Perkins group, which sees £7 billion in annual turnover and is the UK's largest distributor of building materials. City Plumbing has more than 4,500 employees and has close to 400 UK and Irish branches.
Whilst City Plumbing prides itself on being a leader in the plumbing and heating market, with a laser focus on customer service, the company has faced challenges as it relates to using and understanding data to support these goals. The company's Head of Data, Business Intelligence & Analytics, Chris Dean, spoke with diginomica recently about how data silos across the organisation and a lack of internal experts were proving to be barriers to improvement. Dean said:
We have built a reputation for selling quality plumbing products to the trade, wholesale and online markets, but when it came to data and decision-making, our challenge was twofold.
Firstly, teams across our business worked in silos, only accessing data relevant to their needs, resulting in different teams holding different versions of the truth. And with data dispersed and teams failing to share information in a single source, we were unable to make fully informed decisions, and the data we had wasn't able to provide a complete picture.
Secondly, we faced a challenge when it came to expertise in the business: we only have access to a small handful of true data analysts, meaning that when distilling data, teams relied on these individuals for insights, creating a bottleneck in information dispersal. Manual data analytics are incredibly time consuming, so we weren't able to access the information we needed in time to inform decisions.
Simply put, City Plumbing was in a position where it had failed to effectively ‘democratise data' and place it in the hands of the teams and people that needed it.
Centralised company data
Dean explained that the objective for City Plumbing in order to change this was to create a central source of data, making it easy for all teams to access and consume. The company deployed BI vendor Qlik's Sense data analytics platform to achieve this, bringing all of the organisation's key data into a single repository. On the benefits of this approach, Dean explained:
Previously, marketing would focus solely on certain data sets, such as customer account credit, to make decisions regarding which customers to target, while finance would try to look at the bigger picture of demand, albeit with different data and information.
As a result, teams were making contrasting decisions about customer targeting and business direction. But, when data became centralised through the data lake and consumed in Qlik, all teams were accessing one version of the truth.
Plus, centralising and democratising data has streamlined decision making, broken down silos and united teams across business.
Dean said that he knew that once more data was added to the platform, new and informative insights and information would become available to the company.
Our approach was to collate as much data from around the business as possible and add it to our Google BigQuery and Storage Data Lake. So this became not just about answering the questions of today, but also providing the tool with enough data to answer questions we didn't know we had.
Dean added that Qlik offers a "single source of consumable data," allowing everyone across the business to self-serve data analytics and use accurate, up-to-date business stats to inform decision making.
Local pricing to win otherwise elusive business
However, City Plumbing's biggest focus now is on using data to create a personalised, bespoke understanding of the needs of the organisation's customers. Dean explained:
We're trying to use data to categorise and segment the businesses we sell to in order to create tailored actions for each. In the past, for example, we might have targeted 10,000 customers for a marketing campaign, but would typically only see a conversion rate from that campaign of about 5-10%.
Not having a bespoke understanding of individual customers meant we were doing things like marketing to customers who had no credit. Our expectation was that we would use data to better understand the needs and demands of our customers in a more microscopic manner. We needed access to the right information about our customers to change and improve our business decision making.
Targeted intelligence has allowed City plumbing to more effectively personalise its pricing customers across the UK, which should improve the company's competitive position. Dean said:
We have been using the platform to collate data on the local independent suppliers of our customers. By having access to data on things like the prices competitors are offering, our marketing team is able to use geoanalytics to ensure that we're offering competitive prices to our customers in a local area, without changing prices for an entire region.
The upshot of this is we have created an enhanced customer proposition, which improves our profit margin on sales; where we once reduced prices across a region to suit the demands of a few, we can now tailor offerings to individual customers based on the data we have on local competitors.
Dead added that the company is seeing improved efficiency across a number of areas in the business that have embraced the BI platform.
From supply chain and logistics to finance and marketing, we have reduced the time it takes to make decisions, ultimately making the entire business more effective. Plus, by simply consolidating and streamlining our data tools into the one platform, we have saved approximately 60% on exiting unnecessary [software] contracts.
And the central platform has also benefited City Plumbing in its response to COVID-19, to both better understand its financial position and boost operations. Dean said:
As the economic impact of the Pandemic progresses, we have been looking into how we can integrate past data from the industry to get a better understanding of our own sales impact.
Because we've never experienced anything like COVID-19 before, we have to look at economic indices and market data from previous events to establish how demand will change. We have been using data from recessions, where you see collapses in sales, to try and plan for the future. Mining for this type of data and integrating it with our existing insights can help us to understand drastic change.
As well as this, we have been using data to tactically map branches around the country to understand how the pandemic has impacted them and where we need to make changes. If a branch has experienced a COVID-19 outbreak, we have data to understand how that will impact output in the area and can move necessary resources to other branches to continue operating and serving our customers. By plotting this data on maps, we've created a visual tool that has helped us understand any changes to output and deliverables throughout the crisis.
There's no such thing as ‘bad data'
Continuing on Dean's mission for City Plumbing to democratise data across the organisation, his team is assessing how more data can be pulled into the central repository and help inform further actions outside of sales. He explained:
We're making more informed and accurate decisions that improve outcomes. Shifting the decision-making process to becoming data-driven will see the ROI from our investment in BI grow even further. To do this, over the next six months, we would like to further democratise data and bring all departments into the fold. In particular, we'll be looking at HR analytics, using data to inform insight on recruitment and attrition.
Also, our new data strategy fits into our overall digital transformation goal to have more API and real data moving between applications. By updating applications to those with better interconnectivity, we're hoping to accelerate our digital transformation. With broader digital transformation across the business, our data lake will become richer, with more real-time information included-and his feeds into the wider objective to become a truly data-driven organisation.
In terms of advice and key learnings, Dean said that his firm has taken the approach that ‘all data is good data' and that something can be learned from looking at all information across the organisation.
That there's no such thing as ‘bad data'. I've learnt that if you put rules and checks in place on data that is going into the Data Lake, you will end up cutting out so much data that the business intelligence function won't exist.
A key learning for us has been the importance of feeding all data, good or bad, into the Qlik platform in order to gain insights that are fully informed. This process allows us to make decisions that are data-led, abandoning intuition or gut feel, which has ultimately revealed that we make better decisions when we put full trust in data.