our process

Objectives and key performance indicators are unique to you, our process is unique to us. While we customize all our work to meet your direct and indirect business challenges, we trust our own process to serve your needs best and create utmost internal efficiency and efficacy.

Ativo 58@3x

1. disruption kickoff

After receiving your initial brief, we bring together our core team to disrupt our thinking and see what we can discover beyond the obvious. Client team and ignosi team reviews and condenses the key challenges. We then ask propelling questions and review scenarios for getting to a great result. We nail down the most important objectives and give you an overview of our gameplan and joint project. This early on in the process there will be many moving parts, but the key outcome of this meeting is to know what we don´t know. We then go after building a plan for finding that out.

Ativo 57@3x

2. bespoke design

After the kickoff session, we come back to you with a proposal on KPIs and how to achieve them. To make your data-driven insights a reality, we provide you with formats, context, ways of working, team and a concise cost proposal. Depending on the maturity of your data and your particular set of requests, we also provide you with specific variables and data sources that solve for your business challenge.
Ativo 56@3x

3. design implementation

After reading, cleaning, programming and curating your data, we show you the composition of your request with a selection of variables. We now assess interest in your data for third parties – and test against their partner objectives. If it proves useful and usable, we set up your data as a source and create an additional revenue stream for you.

Ativo 55@3x

4. quarterly reviews

We review set-up, dashboards, viability of third party data and our own curated data sources in depth – at least once a quarter on top of the regular project meeting schedule. Data accuracy is a key concern for your internal and external data monetization and these scheduled deep dives have proven essential. In the beginning of our joint partnership, new data insights will drive new questions and set up and a regular review of new insight possibilities will enrich your work and optimize your output.

statistical and analytical techniques

To accurately extract quantifiable data, we use technical and algorithmic approaches that facilitate working with large data sets. We employ advanced analytical techniques and methods, to be able to address data sets from a scientific perspective. Our engineering tools and methods help us wrangle large amounts of data and identify the relationships needed to derive high-quality insights.

Among the techniques used are data mining, time series, machine learning, exponential smoothing, data pattern recognition, mathematical modelling, differential equations, curve fitting, 3D – modelling, parameter estimation, optimization, mathematical simulation, neural networks, factorial analysis (KPIs), genetic algorithm and correlation analysis.