The Digital Practitioner's Almanac - 2
Gaurav Agrawal
Technology and Transformation Sales Leader I Trusted Advisor to Financial Institutions
In Part 1, I discussed three points digital practitioner's should keep in mind, to successfully adopt Digital. The first was the Iceberg Principle, which suggests that digitization of the middle and back office is as important as, digitizing the front end and often requires more effort. The second was the concept of Fail Fast, that proposes there is merit in experimenting quickly and learning from mistakes, as opposed to necessarily trying to get things first time right. The third was how organizations can create the right culture, for digital adoption to succeed. To read Part 1 CLICK HERE.
In this article, I discuss three additional points to keep in mind, when creating and implementing a digital strategy. I have also hyperlinked interesting articles that further talk about some of the points I have mentioned, so do visit those too.
4. Take Moonshots: Google popularized this through it’s ‘moonshot’ projects, that aspire to generate at least 10X impact. Firms must invest efforts to achieve the exponential, rather than just the incremental. For example, Eastern Bank based out of Boston, took on an average of 3-4 weeks to originate small business loans. Guess what a re-imagined process brought the loan origination time down to? ….. 5 minutes! (this is not a typo :-) ). WSJ dubbed it the Coffee Break loan. Achieving 10X impact requires firms to move away from incremental thinking, even trying to be Best in Class, to fundamentally re-imagining outcomes.
Organizational culture is key for moonshots to succeed. Creating a safe environment to experiment, where employees can spectacularly fail, before they can spectacularly succeed is key! Additionally, using digital technologies and concepts of Fail Fast, firms today can increase the probability of success of moonshot projects and do it at a lower cost. Also, businesses today are asset light, prime examples being Uber, AirBnB, Facebook and Google. Being asset light allows faster acceleration to achieve 10X, for example, achieving 10X sales in digital banking is easier than 10X sales in branch banking.
Digital can bring exponential impact to traditional businesses too. If you have ever walked away from a Starbucks line because it was too long and now order your morning cuppa through their app and walk in, pick up and go, you have experienced this transformation. Another powerful example, in asset heavy industries like aircraft engines or turbines, is the creation of ‘Digital Twins’. Digital Twins mimic the working of complex machines, by analyzing data gathered through sensors in real time, and predict actions like proactive maintenance, which reduces the occurrence of highly costly downtime.
Lastly, in the context of Moonshots, there are two paths to success. The obvious is the big idea. The other is incremental steps, but implemented in a finite time, resulting in an exponential outcome. For example, Amazon, Google, Facebook constantly make incremental upgrades to their websites – each update is small, but over a finite period, the results are exponential.
5. Data is the new oil: or the new gold if you like the bling bling! Businesses today are launched on the premise that, profits will be earned by monetization of data generated by the business, rather than selling the core product itself. A new avatar of the old business model, where you sold the razor for free but made money on the blades.
Let me illustrate this through a much talked about future in travel - driverless cars. Data monetization can possibly enable a future where travel is not only driverless but also free! Your driverless Uber has a captive audience in you. Throughout the ride you are immersed with advertisements, which are auctioned to the highest bidders based on data on you (anonymized of course!). Uber makes money from advertisements and your ride is free. Yes you can switch of the advertisements, but then you pay for the ride – your choice!!
So here are how organizations need to think about data:
- Treat data as an asset: Build the right data capture mechanisms - about your customers, employees, products, services, projects and, partners. Protect the ownership of data and its derivatives through legal means. Treat data the same way you would treat intellectual property. Invest in data quality and data governance. Dust the cobwebs on your data.
- Data -> Insight -> Action: I first heard Satya Nadella talk about Data Gravity, a term originally coined by Dave McCrory. Data has gravity and therefore attracts compute power to it. Big Data attracts big compute and you get big insights. The rub is, an abundance of insight stymies action – it’s like the cereal aisle in the supermarket, where too many choices slows action!! Therefore, organizations must enable actionable insight. This is reflected in the rise of analytics use cases around ‘Next Best Action’. For example, a search on Amazon now often marks one of the so many results as ‘Amazon's Choice’. In most cases that’s what I choose and it has helped spur action. Marketing offers based on current physical location spur action. Next Best Action algorithms require training, and enabled by a feedback loop, on what action the user took and how closely it met her expectations, will continue to improve the accuracy of delivering the actionable part of the insight.
- Bi-Modal Data Infrastructure: Increasing organizational decision making agility, requires an agile data & insights infrastructure. In some cases however, reliability trumps agility, for example regulatory reporting. Both agility and reliability are important and organizations need to run in a bi-modal fashion, a concept introduced by Gartner. Systems for risk management and financial accounting need to be reliable. Systems for CRM, Campaign Management, Product creation need to be agile . The way organizations create their data governance process, technical architecture etcetera should reflect bi-modal requirements. And if I can take you back to Part 1 of this article, the concept of building a two speed organizational culture discussed there, couples very well with the concept of building a bi-modal data infrastructure
6. Information Security and Data Privacy Compliance: These are increasingly becoming board level agendas. Like the air we breathe, the importance of these topics is felt acutely, when their absence is discovered! Lack of compliance can very well bankrupt organizations. It has definitely caused the downfall of CEOs, including those at Target and Experian. Here are are a few additional points for your consideration:
- Compliance as a revenue generator: We all talk about the cost of compliance. What if we turn this on it's head and start treating compliance as a profit center. Organizations go long lengths to create competitive differentiation. As more businesses become digital and data driven, information security and data privacy will become a key point of differentiation, one for which consumers will be willing to pay extra.
- Manage infosec and data privacy across your ecosystem: As a chain is as strong as its weakest link, so it goes with info sec and data privacy. You need to comprehensively think about the security and proper use of the data you are responsible for, across all participants in your ecosystem, namely vendors, partners and employees. Some of the most infamous cyber security hacks exploited vulnerabilities in the hacked organization's third party systems, that provided a gateway into the organization's network (e.g. Target, JPMC hacks).
- Managing the greys of data privacy: Info sec is black and white - you cannot let anyone hack your network... period. Data Privacy has a lot of grey's today. One big reason is consumers don't know what they are giving up when it comes to their data, in return for the services they are getting. I believe communication and transparency can help. Both Facebook and Google, which are facing severe regulatory backlash on data privacy, have enabled ways for users to see what data they have on them. Explaining consumers on how their data will be used, can also help manage concerns that consumers are starting to develop on the privacy of their data. For example, a bank on its phone app, asked me to enable phone tracking. It went on to explain that it helps fight fraud - for example they can match my location with the location of a POS transaction. This explanation makes the decision easier for the consumer.
I hope you find the points mentioned in these articles useful. Best of luck for a successful digital journey! If you have any suggestions, ideas that can help organizations successfully embrace digital, please share it as comments.
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6 年I agree with you on the Iceberg theory. Financial institutions have to focus on leveraging the untapped potential of data to generate significantly more ROI. However, I think its not just about the tools and processes that are employed to harness the vast amounts of data produced every day (literally multiple exabytes per day according to one study). Also, with more than 90% of the current data in the world having been produced in the last two years (credit: IBM), its unsustainable to try and use traditional practices to mine it. I believe the industry has understood the lacunae in its data and methods (unrefined, unorganized, un-consumable) and is moving towards Data Quality as its mission objective. Data quality and Data lineage are quickly becoming buzzwords in their own right. An organization that can effectively manage this (a gargantuan project!) will reap the benefits. I recently had the opportunity to attend a talk on this subject by Dr. Peter Weill (Sr. Research Scientist, MIT Sloan) - a man with tremendous insights into Information Systems. - Sameer.