Unpacking the Methodology Behind Industry Insights: CCR’s Media Sector 2023
22 October 2025
Written by Máté Fodor, Impactonomix
The Cardiff Capital Region (CCR) is home to a dynamic media cluster dominated by small, innovative firms and freelancers, making traditional data sources often incomplete. This reflective piece explores how we approached the challenge of accurately quantifying the CCR’s media sector for the 2023 Industry Insights report. We discuss the need for careful definition and methodology, and how a mix of cautious assumptions and creative techniques helped us capture the “ground truth” of this fast-evolving sector.
Defining the Media Sector: SIC Codes and Scope
A first step was to delineate, as accurately as possible in terms of industry practices and expectations, what counts as the media sector in CCR. We adopted the UK Department for Digital, Culture, Media and Sport (DCMS) definition of the audiovisual sector, and then broadened it slightly to include related entertainment software and video games activities. In practice, this meant identifying companies by specific Standard Industrial Classification (SIC) codes associated with film, TV, radio, music, and gaming.
This SIC code definition provided a necessary boundary for analysis, but it is important to acknowledge its limitations. Industry classification is neither exclusive nor exhaustive – some media-related businesses might not fall under these exact codes, and conversely some firms with these codes might engage in broader activities. SIC codes are a practical starting point, but cannot always capture the rich diversity of a creative sector.
Data Challenges: Small Firms, Big Gaps
The next major challenge was data availability. We drew on the FAME database (which compiles Companies House filings) to gather firm-level data on all identified media companies in CCR. However, most media sector companies are small – in Wales, and more generally across the UK and Europe – and not required to disclose detailed financial or employment figures. The UK has no filing requirement at all for sole traders or freelancers, and micro-companies often file only minimal accounts. As a result, our raw dataset was riddled with blanks – only about 15-20% of media firms we extracted had a reported number of employees.The incompleteness of official data extended beyond headcounts. Many firms also omit figures for turnover, wages, or R&D expenditure.
Using registered company data introduces a lack of clarity in geography – a company may be registered in one place but operate elsewhere (or vice versa), and consolidated accounts mean multi-site businesses report everything at a head-office location. We had to navigate these uncertainties cautiously.
A Conservative Imputation Approach
To address missing data, we employed cautious imputation strategies. Rather than plug in potentially inflated estimates, we used median or lower-quartile values from available data as stand-ins for missing entries. For instance, if a particular company did not report its turnover or number of employees, we assigned it the median turnover or headcount of peer firms that did report these figures. This median-based approach ensured that a few large firms (who must report data) did not skew our overall estimates upward.
For other financial variables – such as wages, R&D spending, exports, or profits – we took an even more conservative route. Missing values in these fields were filled using low-end (first quartile or 10th percentile) values observed among similar firms. In other words, we assumed that if a small company didn’t report its R&D or profit, it was likely to resemble the bottom tier of those that did report. By inputting modest figures, we avoided overestimating the sector’s performance. (This aligns with our experience that many creative SMEs have relatively low reportable R&D or margins, even if their innovative output is high.) Leaning toward the lower bound gave us greater confidence that our aggregate numbers wouldn’t over-estimate the sector’s size.
We also manually included key players that standard datasets miss. For example, public service broadcasters like BBC Cymru Wales and S4C operate under royal charter and don’t file accounts to Companies House. To capture their substantial contributions, we manually harvested figures from their annual reports and added these into our dataset. This ensured that the CCR media sector totals weren’t missing the largest institutions based on a technicality in data sources.
Throughout, our guiding principle was to err on the side of under-estimation. This conservative stance was both a methodological choice and an ethical one – we wanted the results to be credible to policymakers and academics, knowing that inflated numbers could do more harm than good. With a cleaned and completed firm-level dataset in hand, we moved on to calculating the media sector’s economic value in terms of Gross Value Added (GVA). GVA focuses on the value actually added by the sector – essentially the sum of profits and wages.
In practice, this means taking each company’s employment (actual or imputed) and multiplying it by a company-specific average wage, then adding the company’s operating profit (approximated by EBITDA from their accounts). The wage component captures the remuneration of labour, while EBITDA serves as a proxy for the return on capital or operating surplus.
This method gives a conservative GVA estimate. We exclude non-cash benefits (like pensions or stock options) from labour compensation, and we don’t count any extraordinary gains, tax credits or subsidies that might boost a firm’s profits. In effect, our direct GVA calculation captures the core economic contribution – cash wages paid to employees and cash profits – while leaving out anything that might overstate the true local value generated. By design, this places our GVA figures at the lower bound of true value added. We felt this cautious approach was appropriate, given the many uncertainties in the underlying data.
Beyond Direct Impact: The Local Multiplier Effect
The total economic impact of the media sector doesn’t stop at the direct GVA. When a production company in Cardiff hires local crew and pays wages, those workers spend their income in the local economy. When a TV studio buys set materials or commissions a post-production service, it creates business for suppliers, some of whom are local. These indirect and induced effects can significantly amplify the sector’s footprint through a local multiplier effect.
To estimate this, we built a simple local multiplier model grounded in regional economic theory. We asked: for each £1 of output in the CCR media sector, how much additional GVA is generated in CCR via supply chains and household spending? Two key parameters fed this model. First, we needed the local sourcing rate – what proportion of expenditures remains in the local economy. Based on surveys and our own contextual knowledge, we assumed about 20–22% of spending is local (in other words, roughly one-fifth of the goods and services that CCR media firms and their workers purchase are supplied from within CCR). The rest leaks out to other regions or imports. Second, we used the regional GVA-to-turnover ratio (τ) to gauge how much GVA is produced per pound of output in the broader economy. In absence of CCR-specific data for this, we drew on Welsh national statistics and survey data, using τ ≈ 0.71 (71%) as an average value-added share. This implies that for local suppliers, about 71 pence of every £1 in revenue ends up as GVA (the remainder being their own input costs). Finally, we made a simplifying assumption that households spend all of their income (i.e. workers don’t significantly save, to focus on maximum induced effects).
With these parameters, we applied a standard iterative multiplier. In essence, we calculated how initial sector turnover circulates: a portion is paid out as wages (household income) and a portion is spent on inputs; in each case only 20% of those expenditures go to local suppliers, of which 71% becomes GVA, which then becomes income for someone else, and so on ad infinitum. Summing this diminishing series yielded an indirect + induced GVA estimate of about £394 million on top of the direct £228 million.
It’s important to emphasize that this model provides an estimate of broader impact, not an exact science. We treated the multiplier output as an upper-bound scenario for what the media sector might be contributing if those local sourcing assumptions hold. By anchoring our assumptions in local data and keeping them conservative, we tried to strike a balance between recognizing the real economic ripple effects and avoiding the trap of inflated multipliers.
Capturing the Ground Truth in an Evolving Sector
Perhaps the biggest takeaway from this methodological exercise is the importance of bespoke, ground-up research in a sector dominated by small and innovative firms. Traditional statistics often struggle to keep up with creative industries, where much of the activity happens in micro-enterprises, start-ups, and freelance gigs. Official datasets can therefore undercount the sector’s size and growth – or miss it entirely. Our approach, compiling firm-level data and intelligently filling gaps, was motivated by the need to get closer to the ground truth of what’s happening on the ground in CCR’s media scene.
By combining Companies House data, public reports, surveys, and government statistics, we could cross-verify our estimates. For example, after calculating our bottom-up GVA figures, we compared them with StatsWales official figures for the region’s economy. This helped ensure our numbers for total media-sector GVA and employment made sense in the bigger picture (and in some cases revealed that using broader regional data as a proxy likely underestimates CCR’s true figures, since CCR is a subset of larger areas used in official stats). Encouragingly, our carefully built estimate showed the media sector contributing about 1.6% of CCR’s GVA, slightly above the UK media sector’s share of national GDP – a finding that underscores CCR’s growing status as a media hub.
Finally, a note on freelancers and hidden talent: our report identified at least 1,830 active freelancers in the CCR media sector. This population is rarely captured in standard employment stats, yet it is the lifeblood of creative production. By incorporating such insights (via surveys and local knowledge), we aimed to shine a light on this informal workforce. It’s a reminder that measuring a creative economy isn’t just about tallying companies or output – it’s about understanding networks of creators, many of whom work project-to-project.
