If we consider a taxonomy of business cases we might include:
- a technology element
- a sector or industry
- particular use case(s)
The particular use case is likely to be conditional on both the technology element and the sector/industry.
Examples:
- PowerBI, (in) Insurance, (for) Financial Reporting
- Neo4J graph database, (in) Pharmaceuticals, (for) R&D: Compound Synthesis Management
The core of a business case is often quantifying the financial value of the work, which is what is discussed here.
Calculating value
tl;dr: We can find value by estimating annual cost savings and capitalising by a suitable cost of capital.
Example 1: Financial reporting at an insurer
Here value derives from time savings. We assume our financial reporting solution saves an estimated 10 senior financial full-time employees (FTEs) a fifth of their time.
| Line | Label | Unit | Value | Note |
|---|---|---|---|---|
| a | Senior finance FTE cost (all in) | £ | 140,000 | |
| b | Working hours per day | Hours | 8 | |
| c | Working days per year | Days | 260 | |
| d | Working hours per annum | Hours | 2,080 | |
| e | Cost per hour | £ | 67.3 | |
| f | Time saving | % | 20% | |
| g | Value of time saving per person per day | £ | 107.7 | |
| h | Value per person per year | £ | 28,000 | |
| i | Number of people in finance team | # | 10 | |
| j | Total annual saving | £ | 280,000 | |
| k | Cost of capital | % | 8% | |
| l | Capitalised value | £m | 3.5 |
Example 2: Enhanced drug discovery in pharmaceuticals
This is a more complex example which is broken down into several sections, reflecting the different workstreams within the project.
Assumptions
As a shortcut to enable us to think about the value generated by the drug discovery, we use the fact that the client has told us that a blockbuster drug can deliver $13 billion of revenue in a year, and estimate that 1/1000 drugs being worked on will be blockbuster drugs.
| Line | Label | Unit | Value | Note |
|---|---|---|---|---|
| a | Blockbuster drug annual revenue ($m) | $m | 13,000 | |
| b | Blockbuster drug daily revenue ($m) | $m | 35.6 | |
| c | Proportion of drugs which are blockbuster | # | 0.001 | 1/1000 |
| d | Daily drug revenue expectation ($) | $ | 35,592 |
Every day lost therefore has an expected value of $36k.
Pipeline for Compound Synthesis Management logistics graph
Here value derives from reliability and we assume that when the graph database is down, the drug discovery process is halted, affecting the time to market for our expected (i.e. mean-average-value) new drug. Our improved ETL/ELT pipelines materially reduce downtime by improving robustness, reporting and observability such that when issues do occur, they can be dealt with — i.e. fixed and re-run — more quickly.
| Line | Label | Unit | Value | Note |
|---|---|---|---|---|
| e | GraphDB is out of action before our work | # | 0.14 | weeks |
| f | GraphDB is out of action after our work | # | 0.036 | weeks |
| g | Work days in year | Days | 260 | |
| h | Delta as work days in year | Days | 27.9 | |
| i | Value based on assumptions | $ | 991,493 |
The reduction in downtime of around 75% has a value associated with it of $991k.
Dashboards for management reporting
Here value derives from time savings across both producers and consumers of management information. The assumption here is that self-service elements of the dashboard allow consumers of management information to answer questions through their own investigation, without sending the preparer queries on an ad hoc basis. Furthermore, much of the production of management information is now automated. We assume that both producers and consumers of management information have time costed at $2k per day and that there is one producer and ten consumers. Reporting is approximately monthly with different reports being used at the half-year end, such that the report in question is produced ten times over the course of a year.
| Line | Label | Unit | Value | Note |
|---|---|---|---|---|
| j | TS: KPI/reporting preparation time | $ | 20,000 | $2k/day |
| k | TS: directors, recipients of KPI/reporting | $ | 60,000 | 3 days 10 directors |
| l | Value attributed to time saving | $ | 80,000 |
(1): TS is time saving.
Our dashboards save $80k-worth of time.
Robotic laboratory machines log files
Here value derives from higher utilisation of robotic laboratory machines. This higher utilisation is achieved through the ingestion and analysis of log files which are generated on the machines themselves. We assume that inefficiencies such as the machines not working properly — improper de-capping of the acoustic tubes — can be reduced. Robotic laboratory machines are very expensive, and so $500k per year reflects both running cost and depreciation.
| Line | Label | Unit | Value | Note |
|---|---|---|---|---|
| m | Assumed cost of machine per year | $ | 500,000 | |
| n | Number of machines | # | 5 | |
| o | Improved efficiency | # | 0.02 | |
| p | Value attributed to improved efficiency | $ | 50,000 |
We assume 2% efficiency improvement, with an associated saving of $50k.
Capitalised savings
| Line | Label | Unit | Value | Note |
|---|---|---|---|---|
| q | Total ($m) | $m | 1.12 | |
| r | Cost of capital | % | 8% | |
| s | Capitalised | $m | 14.0 |
The sum of annual savings capitalised comes out at $14m.