Technological advancements in recent years have forced companies to keep abreast of these trends for their mere survival.  

In fact, according to a McKinsey study, this has been all the more important during COVID-19, which has pushed companies beyond their digital technology tipping point. Whilst one of the unintended by-products of this virus has motivated companies to jumpstart their technology strategies, some frictions to adoption and implementation continue to exist. This recent article in Forbes highlights seven challenges that large corporations navigate  when embracing and implementing company-wide digital transformation:

  1. Failure to address inertia - staying in the ‘comfort zone’ and continuing with the ‘status quo’
  2. Lack of digitally-savvy C-Suite executives
  3. Lack of effective organizational change management
  4. Lack of modern processes preparedness (i.e., still in the ‘dinosaur’-age of operations)
  5. Inability to curb the digital enthusiasm (and ambition)
  6. Confusion between (digital) optimization and transformation
  7. Roadblocks due to regulatory compliance

The list above is not surprising to us at idaciti.

We have heard many companies, first hand, express the same sentiments.  Moreover, these challenges are pain points we have committed to addressing head-on.

The urgency with which companies in the ESG ecosystem must act to collect data in order to help companies and society as a whole respond to the climate and environmental crises cannot be further underscored.

This is why we recently released our ESG Accelerator Solution - to help companies fast track their ESG data structuring processes and start to realize ROI in weeks, not years.

The XBRL-First Approach and ML-Assisted Technology Automate Unstructured Data Collection

We have specifically designed and streamlined the on-ramp for companies to quickly adopt and integrate our proven technology platform to hit the ground running and start structuring ESG data within their production environments. Our easy-to-use platform allows business users to structure data and immediately capture all metadata and traceability of the data point back to the source location. In addition, business users can train the ML models to auto-structure large volumes of data within minutes, not hours, days, or weeks.

Our goal is to ease the fear held by many organizations that digital transformation may be ‘too disruptive to the existing processes’ by offering these same companies a production-ready pilot program to help their teams adopt new technology into their existing platform and quickly realize a return on their investment, with minimal investment in resources, time and risk.

Rapid Acceleration is Needed of All Front to Keep Sustainability Goals within Reach

Disruptive innovation has been at the core of our culture since the beginning of the 21st century. From the proliferation of smartphones, the omnipresence of social media to self-driving cars and 3-D printers.

Isn’t it time to jump onto the ESG highway and accelerate your way into the digital transformation age?