FountainBlue's November 1 VIP roundtable, on the topic of 'Data is the New Black'. Thank you also to our gracious host at Automation Anywhere. Below are notes from the conversation.
Here's the thing about data:
There's a wealth of it, and it's just getting overwhelming bigger.
It drives everything - every industry, every person, every company.
It's good news for the semiconductor industry and other sectors which make sure that we have the storage, the energy, the network needed so that people can keep getting access to that data.
Data within legacy systems might be valuable, but it is likely also difficult to access.
Data across multiple sources might be useful, but it is likely to connect data across multiple source into a common dataset, useful enough to understand problems and make decisions.
With that said, here's the challenge and opportunity around data.
There's so much of it that we need to filter it first to identify which data is relevant and then also for what we need immediately, what we need in the short term, and what we might need in the long term.
It takes a lot of energy and resources to keep the data, so we must be strategic about what data to keep and how we can efficiently get it into the hands of those who need it most.
Compliance to security and privacy issues make data management high-stakes for all.
Having an interoperable standard for data sharing might help better integrate data across sources, teams, companies, industries.
Customers today are empowered and fickle. Companies must be able to innovate and customize more quickly to serve their needs.
Even adopted solutions have much shorter life cycles today, as customers want solutions which are better and faster and more battery efficient.
People are at the heart of the problem around data privacy. They want their privacy and their access. It's hard to give people both at the same time every time.
Below are some shared best practices:
Make a plan on how data is gathered, managed and distributed.
Plan for a future with much more data. Be selective about what data is important.
Collaborate with other people, companies and industries and share best practices.
Focus your data plans on the needs of your customers and your partners.
Consider the intentions and ethics around the people and companies providing the data.
Policy may not be the answer to managing data mishandling. Indeed, it may cause more complications, less fairness.
People should be responsible enough to know how their data is used and astute enough to take the data they receive with a grain of salt - even to the point of questioning the validity of the data and the intentions of the party providing the data.
Create solutions with tiny form factors to better address the needs of demanding customers.
Ask for less information from customers when you ask them to sign up for something - the less friction you're providing to the customer experience, the better results you could get.
There will be a growing convergence of tech and ethics and values. Speak to the elephant in the room - facilitate that conversation between stakeholders within and across organizations.
Use fewer resources to manage 'garbage data'. Yes, all data might one day be useful, but focus on the data that's more likely to be useful, now and soon, rather than data which might one day be useful.
Below are thoughts on the future opportunities.
The future may have more self-learning - e.g. more AI, less raw data.
Use ML to identify patterns early enough to address and even prevent diseases.
Making sense of unstructured data provides huge opportunities.
The bottom line is that data is everywhere - the use of access and usage are complicated, the stakes are high - you want to give the right people immediate and full access without compromising the integrity and accuracy of the data, and while respecting the privacy of those who 'own' the data.