We have done used our knowledge and experience in many different ways. Here is some of the work we have done with previous clients. These are bespoke solutions that uniquely benefitted them.
Vodafone was going through a major global infrastructure investment project. This involved multiple countries with multiple channels of investment which meant there was over a thousand business cases that needed to be appraised and the project required the ability to summarize these over different dimensions such as region, channel, country, etc.
Create a Golden Source of data for employees within a major technology transformation project within Deutsche Bank. The transformation project had multiple work streams which affected different areas of the organisation structure. The golden source of employee data had to identify where the employees were on the organisation structure and what work streams affected them. This would be used for work stream baseline calculations to gauge the employees that fell under the scope of the workstream. The dataset had to be version controlled to reflect the changes made in the programme.
Create a data/financial model that shows the state of enterprise data storage. The model should give the ability to slice data by different dimensions such as line of business and type of hardware. The model should also summarise the current global view of storage and predict the future storage requirement based growth. The model should be able to run different scenarios to highlight what would happen in these alternate realities.
Automate a manual process which consolidated data from 3 different patient information systems. The final data set was according to national data set standards. The process would be automated from the extracting the data to creating the final data set.
Replace a paper based data collection system with an online web application. In the existing system, paper based records were faxed to a central location for review and updated and gathered onto a master Excel spreadsheet. Due to the nature of the operation this process was error prone and users spent a lot of time validating data. Resources were spent on security due to the sensitive nature of the information such as locked rooms and secure lines of communication.
Take a list of 10,000+ stock price movements and group them into similar transactions. Once the transactions were grouped, run simulations to infer the best trading strategies for specific categories of transactions. Once the best trading strategies were figured out, run optimization algorithms to infer the best parameters for the trading strategies to minimize risk while optimizing profit. All this to be put into a standard reporting format for further analysis.
Extract Skype's general ledger held on eBay's ERP system. The data had to be complete, balanced and validated by stakeholders in both Skype and eBay for accuracy and completeness. The number of transactions far exceeded Excel's capacity of 65,000 rows at the time so Excel had to process text files that held the data.
Migrate all historical data from SAP R3 to a new M3 ERP system for 4 main SAP modules. The complete data set had to be put into a format that could be easily uploaded to M3 ERP system in a standard format. For each module, data for closed and open items and header and detailed information had to be extracted and put into a standard format for upload.
Of course these don't capture the nuance which is why you need to get in touch if something interests you. We are active on social media and would love to hear from you.