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Making Accountants Digital Enablers (MADE)
Last registered on November 15, 2019

Pre-Trial

Trial Information
General Information
Title
Making Accountants Digital Enablers (MADE)
RCT ID
AEARCTR-0005006
Initial registration date
November 15, 2019
Last updated
November 15, 2019 10:37 AM EST
Location(s)

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Primary Investigator
Affiliation
Northumbria University
Other Primary Investigator(s)
PI Affiliation
RA
PI Affiliation
RA
PI Affiliation
Co I
PI Affiliation
Co I
PI Affiliation
Co I
PI Affiliation
Co I
Additional Trial Information
Status
In development
Start date
2019-09-01
End date
2020-08-31
Secondary IDs
Abstract
There is a growing appreciation for the use of technology in UK SMEs to remain competitive. This is evident from the recent CBI report “From Ostrich to Magpie” that claims improving UK companies’ adoption of existing technologies offers a unique opportunity to raise SMEs business productivity. The report highlights improving management best practice, innovation and diffusion, acknowledging the need for businesses to learn and apply new knowledge.

Given that 75% of SMEs use an external accountant (ICAEW, 2014), a programme which focuses on 'Making Accountants Digital Enablers' (MADE) could reach a high proportion of SMEs through existing channels. The accreditation bodies, as well as large firms, such as Sage (UK) Ltd are a route to engage, recruit, train and interact with a large proportion of accountants.

This is a non-business led trial designed by academics at Newcastle Business School, Northumbria University, in collaboration with Sage (UK) Ltd. Northumbria has developed the project infrastructure, will manage and drive the research and co-ordinate the dissemination of findings.
External Link(s)
Registration Citation
Citation
Erfani, Dr Goran et al. 2019. "Making Accountants Digital Enablers (MADE)." AEA RCT Registry. November 15. https://doi.org/10.1257/rct.5006-1.0.
Sponsors & Partners

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Experimental Details
Interventions
Intervention(s)

The project will focus on the provision of an intervention for accountants to better equip them to provide knowledge, skills support and confidence to their SME customers so that SMEs feel better able to harness the benefits of digital technology across several specific applications.

We will use a randomised controlled trial (RCT) to compare different intensities of advice provided by accountants to SMEs (as well as no advice at all: to the control group). Using mixed methods we will evaluate statistical measures of changes in productivity, as well as conducting a realist evaluation of how the transfer of knowledge to SMEs is diffused to drive digital adoption.

Sage will recruit N=390 accountants (not just those that use Sage products) who will in turn will identify 5 of their closely matched SME customers to take part in the trial, totalling N=1950 SME participants.  Of the 5 SME participants identified by each of the accountants. This represents a large robust sample, and as discussed in detail later, gives excellent statistical power with respect to identifying even subtle changes in SME productivity across intervention groups.


Intervention Start Date
2020-01-01
Intervention End Date
2020-02-29
Primary Outcomes
Primary Outcomes (end points)
The two primary productivity measures include: (1) number of invoices (2) revenue per invoice.

Once we know the nature of the historic data it may be sensible to look at a small number of secondary supporting / complementary productivity statistics, drawn from but far from exhausting the following list:

Measurement Rank 1

» Survival
» Revenue per Employee
» Revenue per No. Invoices
» Revenue per Total Assets
» Revenue per ICT Assets (ICT Assets is an estimate)
» Revenue per R&D Spend (R&D Spend is an estimate)
» Change in Creditor Days (Trade Creditors in the last quarter * 365 /Revenue)
» Change in Debtor Days (Trade Debtors in the last quarter * 365 /Revenue)

Measurement Rank 2

» Growth in Average Order Value (Revenue / No. Invoices)
» Growth in No. Customers
» No. Invoices per Employee
» No. Invoices per Total Assets
» No. Invoices per ICT Assets (ICT Assets is an estimate)
» No. Invoices per R&D Spend (R&D Spend is an estimate)

Primary Outcomes (explanation)
N/A
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The primary outcome is productivity of SMEs following an intervention of knowledge transfer via an accountant. The focus of the evaluation is whether training accountants on digital technologies as a route to disseminate information on, and support SMEs in, digital adoption leads to increased productivity.
Experimental Design Details
Not available
Randomization Method
Northumbria will use the SME Matrix to assess the five SME customers by key characteristics from each accountant. Critically each accountant and their consultation of SMEs will be assigned to only one arm. The reason for this is ethical, relates to business ethics recognising that accountants would find problematic to offer different levels of advice across SMEs.
o The digital savviness match of the accountant and the SME
o The spread of SME digital savviness.
o The SME profile based upon the SME Matrix characteristics.
This will generate a sample of n =1950 SME customers to take part in the trial.
The consequence of assigning as accountant and their associate five SMEs to one arm requires us to find similar consultations to be placed on the other two arms, in order to balance out the study.
The Randomized Block Design (RBD) will contain three arms (two treatment groups and a control group). The two treatment groups represent two intensities of training that the accountants receive and disseminate to the SMEs: foundation and transformation (with transformational having additional enhanced features over foundation). Accountants will be allocated then two arms using a process of randomisation, which ensures that the number of accountants and associated SMEs is equal on each arm and through statistical testing that the characteristics discussed above are balanced.
Randomization Unit
The unit of data collection is the accountant and five associated SME customers. the unit of data analysis is the SME, since the study relates fundamentally to changes in SME business productivity. Nevertheless, other supplementary business information will be collected using both quantitative and qualitative means. The treatment was clustered at the level of the accountant.
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
390 Accountants
Sample size: planned number of observations
390 Accountants each with 5 SMEs = 390 x 5 = 1950 We intend to collect eight quarters of historic productivity data from each SME, plus three quarters of data 'during' the period of the study, plus one further quarter 'post' study = 12 quarters of productivity data per SME. as a consequence we will be calculating 23,400 measurements for each identified productivity change statistic.
Sample size (or number of clusters) by treatment arms
130 Accountants per treatment arm x 5 = 650 SMEs
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Please see the attached for a range of estimates for the minimum detectable effect size under different assumptions and ways of treating the multiple comparisons problem. these etsimates
Supporting Documents and Materials

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IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
The Cross Government Trial Advice Panel
IRB Approval Date
2019-03-28
IRB Approval Number
N/A
IRB Name
Northumbria University Ethics Committee
IRB Approval Date
2019-02-01
IRB Approval Number
N/A