DataDiligence was founded on a seemingly simple premise:
data is valuable.
Making the intangible tangible
Data is valuable.
But, data’s value is hard to unlock. It's not reflected on balance sheets. And data projects are, notoriously, failing (80% of the time, according to Gartner).
Also, while many investors & executives intuitively understand data’s value, data itself and the ‘ecosystem’ surrounding it is not being rigorously assessed within commercial due diligence. Nor is data being actively built into business strategies beyond a misconstrued dotted line to IT spend.
We aim to change this.
At DataDiligence, we help businesses & investors identify, extract and monetise the consumer, product and operational insights buried in their data.
Best of both worlds
Chelsea is a senior communications, investor and corporate relations executive with a 20-year track record as a trusted executive and advisor within private equity, M&A, professional services and consulting.
Hongya Liang is an experienced data scientist. She has helped many traditional businesses along the digitalisation process to adopt innovative analytics to realise business potential.
Adam is a senior data science manager with 10+ years of experience from large corporate, consulting and start-up worlds. He has built his career on using data science to solve challenging business problems.
Having completed a Masters in Mechanical Engineering (Mechatronics), Zbigniew recently rekindled his love of mathematics by immersing himself in the applications of AI & ML advanced analytic solutions.
Daniel is an experienced data scientist having worked as a research assistant and intern in the fields of space and atmospheric science. More recently he has turned his analytical expertise towards business.
Client & Partner Success Lead
Leoš is an experienced project, product, account manager and customer success lead with proven results.
He joins DataDiligence as Client & Partner Success Lead.
Only by truly understanding data's value - both strategic & operational - can investors determine its future potential to inform their pricing parameters
Data projects must solve business problems, otherwise the results are scattered & diluted. Data strategies need to be designed to reinforce the business strategy and result in material outcomes.
Implementing data projects is hard. But when effectively managed, they can be transformational, leading to improved decision making, operational efficiencies and - sometimes - new revenue streams.
Our journey so far...
DATADILIGENCE IS FOUNDED
A 'wing and a prayer'. Probably! But we believed from the start that we'd struck a compelling idea and identified an apparent market need - and niche. But being a start-up and category creator is no small feat. So, we gave ourselves a year to test the concept with the market.
PILOTING FRAMEWORKS & APPROACHES
We called in multiple favours from friends and past colleagues to test our ideas and methodologies - even our pitch decks! We can't thank these people enough, for their time, enthusiasm and patience.