Background

The Digital Marketplace is helping those transforming public services by making it simpler, clearer and faster for them to buy what they need. G-Cloud focuses on cloud-based services.  Since its launch in 2012, it has evolved through multiple iterations, with the current version being G-Cloud 9.

So, the introduction of a set of categories in G-Cloud 9 provided a natural step forward.  These offered a level of granularity below the three lots of Cloud Hosting, Software and Support. As a result, buyers are able to find and compare groups of suitable products more easily.

Yet there is plenty of opportunity to further simplify the buyer’s task in future G-Cloud iterations. For example, around price comparison.

Opportunity to simplify pricing

To illustrate the point, let’s take just one of the new categories (Security Testing) under Cloud Support. What we find, per the lollipop chart, are 49 distinct pricing approaches adopted across the circa 4,000 services.

Let’s dig a little deeper, and take a closer look at the actual prices.

The majority of the Security Testing services adopt a per-person-per-day pricing approach, so we’ll narrow the focus to those. This usefully minimises any variability in what one gets for the price, so we’re closer to an “apple-for-apples” comparison.

Each of these services has a range of rates reflecting the seven levels of the standard rate card. And the chart below reflects the prices at the lower and upper ends.

The blue violin plots, reflect the density of the services at different day-rates, and are augmented by embedded box-and-whisker plots. These show that the rates with the highest density of observations fall at around £400 and £1,200 per-person-per-day.

The takeaway

So, what can we conclude from this?

• For buyers, future iterations of G-Cloud could constrain the number of available pricing approaches per category. Combined with a tightening of category scope, where appropriate, the Government could thereby simplify buyer comparison.
• For suppliers, this could also simplify benchmarking and thus enhance price competitiveness.

R tools used

	Packages	Functions
	purrr	map_df; map
	rvest	read_html; html_nodes; html_text
	dplyr	select; arrange; filter; count; mutate; if_else
	tidyr	gather; separate
	stringr	str_replace; str_trim
	tibble	tibble
	lubridate	today
	ggplot2	theme_set; geom_violin; geom_boxplot; geom_text
	forcats	fct_infreq
	ggalt	geom_lollipop
	ggthemes	theme_ economist

Citations

R Development Core Team (2008). R: A language and environment for
statistical computing. R Foundation for Statistical Computing,
Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org.

Contains public sector information licensed under the Open Government Licence v3.0.

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