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Work Blur


Financial Reporting & Transactions

A large multinational in the financial services industry planned to insource it's implementation of the new financial reporting standard - the project involved getting multiple departments to onboard to a system in 24 countries. The key to success was spending significant upfront time in each meeting to ensure that the diverse parties were all talking about the same thing.

Secondary was the focus on the data model - a sustainable data model is always better than thousands of lines of code.

We specialize in Tullinsky at having people who can cross over between different disciplines - and understand the different jargon used by different departments.

Saving a Core System

Do you have a core system developed by a talented employee? What happens when that employee wants to move on?

Identifying crucial systems built in siloes, upgrading documentation, ensuring that the system can be maintained by other staff; and that those staff will be engaged and interested - these are fundamental to keeping the expertise you've generated in-house and allowing your talent and business to grow.

Wrong way of digitalization 

A HR department of an international corporation decided to implement a chat bot to reduced the workload of the HR representatives, so they won't have to answer the same questions all the time. Estimated cost reduction potential - lower six digits euros. They approached IT department for support. Regardless the potential, the selected solution should be the engine available for free.Instead of implementation of a proper basic natural-language-processing (NLP), the mapping of text phrases method was chosen. Already in the testing phase the issues where detected, yet instead of revising the approach, the management decided to proceed. 
- Almost a year of an effort spent on a project that was setup and approached wrong way from the beginning

- Instead of reducing workload of HR department, not only HR department was working overtime to create and maintain the mapping table, but also IT department spent a lot of hours working for a doomed cause.

Automation done right

A multinational industrial company used a manual process for data maintenance and transfer for project management and report generation. With implementation of robotic-process-automation (RPA) all of the data movements and conversion was automated. ADDED VALUE:
- Freed up multiple thousands of hours of valuable employee time a year

- Due to automation only happening on the transition / data conversion level the acceptance by employees was very high, as it neither change their basic working routing, nor required them to learn new tool.

- Reduced volatility and risk in the process

Artificial Intelligence?

We can help you get the best out of your data without buzzwords.

We argue artificial intelligence (mostly neural networks) is just fancy pattern matching - image and voice recognition have been it's biggest success so far.

Predictive analytics? This is application of generalized linear models (GLMs); technology over sixty years old - very useful if you can get your data clean.

Setting business objectives and helping understand the data you have are core to success in data & analytics.

Sometimes it's better just to act 

A department of a big corporation with multiple branches and dozens of teams was heavily involved in reporting cycle. A lot of employees were creating reports on one side, but also evaluating a lot of reports from other teams and departments and using this data to create new reports. The total number of reports close to three hundred. The long and complicated project was initiated to evaluate which reports are useful and how to reduce the number of reports and therefore an effort the employees put in them. The project lasted over seven month. Interviews were held and reports analysed. In the final phase there was an agreed on by all parties involved and approved reduction of reports by 10% on a table. 
Shortly before switching off the agreed reports, another idea was suggested: switch all reports at all and see, how many complaints will it raise. The management of the branch agreed to participate in this experiment.

- After the first month only about 5% of reports were missed and activated again.

- After a nine months a total of 12% were reinstated in original form of with minor adjustments.


- An immense amount of time saved for employees on all levels up to management.

- Reduced risk of miscommunication, as due to the reduced number of reports the data became more reliable.  

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