The world of banking, financial services, and insurance organizations have faced a complete paradigm shift in the last 24 months. FinTechs, TechFins, Digital Transformations, and more are disrupting the industry and the key to maintaining the competitive advantage is unlocking the value of data sprawled across the institution. Maybe you’re a CDO, CIO, CTO, Head of Data Science, etc. – regardless of the title, you’ve been asked to “weaponize your data”. Where do you start?
- Help! I’m lost in an alphabet soup and don’t know where to begin – AI? BI? ML?
Data isn’t new and neither is the idea of business intelligence. Data warehouses, reporting, dashboards, scorecards – you name it – have been around for a long time. However, the modern experience requires a new approach because of how much has changed and evolved.
The explosion of data and the speed of business has created a nexus where companies need to know what’s going to happen before it occurs. Data science driven solutions are being sold on every corner, and every business feels they need an AI strategy to compete – but you can’t put the cart before the horse. A robust data strategy is required to build intelligence before you can support hyper intelligence and science.
Look for ways to push your data into active decisioning rhythms. Accelerate the intelligence of your business around data and let the natural evolution towards machine learning and artificial intelligence occur. The basics haven’t changed – the right information to the right people at the right time has been the foundation of data intelligence. Start small, review the impact, get more comfortable with the impact of data-powered intelligence, and look at ways to create more impact.
- Ok, but I don’t know where my data is. My analysts spend half their time just trying to find everything and then bring it to Excel – how am I supposed to get the right data if I don’t know what I have or where it is?
Data sprawl is real, but there’s a solution. In a word? Governance. It’s easy to say everyone needs data governance, but the actual implementation of robust governance programs tends to fail more than it does succeed. First and foremost, when you look up at the data mountain, it gets overwhelming, and many groups tend to kick the can for more ready wins. Second, a lot of companies just fail to understand what it means – is it just cataloging? Is it data quality? Is it compliance and access?
At its core, data governance is really meant to be a means for the business to take ownership of its assets. Technology teams can shift into an enablement mechanism, and the business can take the lead in defining the people, processes, and definitions of what the data represents.
New technologies in the cloud enable agile execution and implementation of data governance solutions that take a lot of the grunt work off a business’s plate. Starting small and letting the value of governance present itself sooner rather than later is a great first step to getting rid of sprawl and getting your data in a usable state.
- This sounds like a lot and my IT department is understaffed and underwater. Don’t they have to do everything? Who owns and manages our organization’s data – the business team or the technology team?
So, you know you need to get back to basics of defining the “why” of my data, and you need to get your arms around what data you have and what it means. Now the question becomes, who’s responsible? For a long time, data was seen as a technology system and asset – database systems were technology team purview, processes generating data were applications maintained by technology, reports being created for the business were created by the technology team.
As Lee Corso might say, “not so fast, my friend”. Data capture, use, maintenance, definition, analysis, etc. are now all the purview of “the business user” more so than the technology. Data is a business asset. Period. As a business asset, the business is responsible for defining the data, governing the data, and maximizing the ability of the data. That doesn’t mean technology teams aren’t involved – compliance, security, operations, BCP and DR, evolution and scale – are all facets the technology teams must partner with the business to execute. However, to truly recognize the value of data, the business must own it as its core asset.
- Ok, but what about data that isn’t even in my department? What if I want to use our partners’ datasets? How can I use other datasets more easily as a 2nd or 3rd party when the data contains sensitive information?
Data sharing is being thrust to the forefront of “what is old is new” regarding data trends. The increase in both direct regulatory actions (think CCPA and GDPR) and the sensitivities around consumer information privacy and transparency have created a paradox. On one hand, businesses need to be able to share data in an ecosystem to create a fully fleshed out view of their customers’ profiles and needs. On the other hand, businesses are loath to share their data for privacy concerns and exposure risk.
So how to kill two birds with one stone?
Leaning into the cloud and what it does best – sharing compute and storage in a secure manner. Modern cloud technologies have enabled a business to share data without sending data and do-so in a manner that still protects consumer identity. There is power in data, and there’s power in data exchange.
Data exchanging shouldn’t be about moving data around (extract to csv, zip file, encrypt file, send file, receive file, decrypt file, unzip file, load file…). Data sharing should be about storing once, creating points of secured access, then enabling connectivity. Modernizing your data means bringing the model to data and not the other way around.
- This sounds like a lot of work, and I don’t exactly have a lot of staff. How am I supposed to build and retain a data team?
“The War on Talent” is at the top of almost every organization’s mind right now. The last 24 months have flipped the world on its axis and we’re seeing large migrations of talent move every direction. To double down, the speed of cloud and data technology has outstripped the ability for most companies to maintain the knowledge, skills, and certifications required to harness the new capabilities that become available.
If you make the decision to build your own team, then it’s paramount to partner with your people organization and create a robust learning and development program, centered around building and using knowledge capital. Having leadership that can draw career paths and trajectories, facilitate active projects to create points of exposure to the new technologies, and building compensation and variable bonus pools around learning are critical to stimulate ongoing skill development. Retaining talent requires a culture that supports the same and speaks to talents’ desire to work with purpose.
A lot of that is easy to type, but hard to execute. It’s why I have always leaned into strategic partnerships that allow me to balance my organization’s needs with the budget, plan, and overall strategic goals around people and abilities. Finding the right partner(s) allows your organization to focus on your strategic goal and trust the partner is focused on their talent, skills, certifications, and training. Look for partners that want to build and partner with you to build an effective data journey vs just putting bodies in your office.
- Ok. So, let’s assume I get all my ducks in a row – I still must “weaponize the data”. How can I use data to innovate my business?
Once the right data architecture – technology and resources – are in place, you’ll see the gains in knowledge capital, efficiency, collaboration, risk mitigation, productivity, and overall performance. Once you’re able to use data, then you can *use* data. Making data pervasive throughout the organization and more accessible has tangible results. For example, increasing the usability of data in Fortune 1,000 companies by just 10% could create:
- $2 billion increase in total revenue each year
- 16% increase in return on equity (ROE)
- 1.4% increase in return on invested capital (ROIC), increasing net income by $5.4 million
- 0.7% increase in return on assets (ROA), adding $2.87 million of value in fixed assets
Those are all great signposts that you’re on the right path. The right data architecture also opens the door to the powerful combination of human and machine intelligence. Once you’re able to use your data effectively, evolve the data and processes towards bespoke combinations, new avenues open for innovation. Creating shareable datasets and placing them in marketplaces. Combining insights across your organization and other organizations to rapidly evaluate new products and offerings. A full, 360-degree view of your customer can open new patterns for retention and add-on sales.
Anand Pandya, Global Head of Financial Services at Hakkoda, Inc.
Anand serves as the Global Head of Financial Services at Hakkoda, and, as such, he is the primary leader in the industry sector to design, build, and manage modern data platforms for banks, lenders and financial institutions. With 20+ years of experience leading global teams across technology firms, Anand’s experience has nurtured him into a transformational leader with foresight and creativity. Prior to serving as Chief Data Officer at Curinos and leadership roles within Informa Financial Intelligence, Anand served as a data, analytics, and intelligence consultant to Fortune 1000 companies across the United States. As a career long data advocate and evangelist, Anand has been responsible for transforming data management, governance, and analytics practices, developing new FinTech products and services, and rooting himself in the belief that innovative thought strikes best over a piping hot cup of coffee.