The race to digital is heating up in financial services (FS) organizations; increasingly, the engine making this happen is Agile. Why? Quite simply, it is software that makes any financial business truly digital. Organizations are therefore in a rush to become great at rapidly innovating, developing, and delivering new software products to win new clients and retain and serve existing ones.
Oliwia Berdak and I have just published twin reports — one for eBusiness and channel strategy professionals, and one for AD&D leaders — that share our findings on how FS organizations are trying to ramp up their digital innovation capabilities rapidly by leveraging Agile and other innovative models.
Our key finding comes in response to a question: Are you building a digital lab that contains great developers but is isolated from key business leaders and other technology management teams? If the answer is yes, don’t! If separate digital units pursue disruptive opportunities, they will often end up with just front-end apps or proofs of concept that are impossible to integrate and scale with same speed they were developed.
Exposed brick is replacing marble at many banks, insurers, and payment firms. Warehouses are deemed a better location for digital labs, digital centers of excellence, innovation labs, and innovation centers. But why are these spaces proliferating from Silicon Valley to Singapore?
A cynic could say it’s a marketing exercise aimed at making the respectable (if a little slow) financial institutions seem more innovative — and more attractive to both customers and developers. But it’s more than that. Frustration and ambition are pushing business executives out from their traditional locations.
Digital labs promise speed by unshackling product and software development from slow business, technology, and compliance processes. They embrace new approaches, such as design thinking, customer centricity, and Agile development. They can drastically cut the time it takes to develop a proof of concept (POC).
But that’s where the dream ends.While these separate digital units aim to be disruptive, they often deliver just front-end apps or proofs of concept that are impossible to integrate and scale. Why? Because software-driven innovation requires a connection to systems of record, rigorous testing, an understanding of security and compliance threats, an analysis of impact on business units and revenue, and someone with the resources to own, love, and keep developing the product — all the things that made digital innovation so slow in the first place. All that labs achieve is to postpone these reality checks.
Today’s customers, products, business operations, and competitors are fundamentally digital. Succeeding in this new era mandates everyone constantly reinvent their businesses as fundamentally digital. You have two choices,
· become a digital predator; or
· become digital prey.
To compete in this new digital market norm, software applications and products must contain new sources of customer value while at the same time adopting new operational agility. I&O pros need to change from the previous methods of releasing large software products and services at sporadic intervals to continuous deployment. All must adopt key automation technologies to make continuous deployment a reality.
Consumers (and B2B customers) are more and more empowered with mobile devices and cloud-based, all but unlimited access to information about products, services, and prices. Customer stickiness is increasingly difficult to achieve as they demand instant gratification for their ever changing tastes and requirements. Switching product and service providers is now just a matter of clicking a few keys on a mobile phone. Forrester calls this the age of the customer, which elevates business and technology priorities to achieve:
Business agility.Business agility often equals the ability to adopt, react, and succeed in the midst of an unending fountain of customer driven requirements. Agile organizations make decisions differently by embracing a new, more grass-roots-based management approach. Employees down in the trenches, in individual business units, are the ones who are in close touch with customer problems, market shifts, and process inefficiencies. These workers are often in the best position to understand challenges and opportunities and to make decisions to improve the business. It is only when responses to change come from these highly aware and empowered employees, that enterprises become agile, competitive, and successful.
The age of the customer demands more of companies, forcing them to change how they develop, market, sell, and deliver products and services. In response, CIOs must invest in business technology (BT) — the technology, systems, and processes to win, serve, and retain customers. At Forrester’s Forum For Technology Leaders in Lisbon (June 2-3), leaders from firms like BMJ, Portugal Telecom, BBVA, Mastercard, Alliander, DER Touristik and UniCredit will share strategies that you can use to achieve Read more
Formula One has gotten us all used to amazing speed. In as little as three seconds, F1 pit teams replace all four wheels on a car and even load in dozens of liters of fuel. Pit stops are no longer an impediment to success in F1 — but they can be differentiating to the point where teams that are good at it win and those that aren’t lose.
It turns out that pit stops not only affect speed; they also maintain and improve quality. In fact, prestigious teams like Ferrari, Mercedes-Benz, and Red Bull use pit stops to (usually!) prevent bad things from happening to their cars. In other words, pit stops are now a strategic component of any F1 racing strategy; they enhance speed with quality. But F1 teams also continuously test the condition of their cars and external conditions that might influence the race.
My question: Why can’t we do the same with software delivery? Can fast testing pit stops help? Today, in the age of the customer, delivery teams face a challenge like none before: a business need for unprecedented speed with quality — quality@speed. Release cycle times are plummeting from years to months, weeks, or even seconds — as companies like Amazon, Netflix, and Google prove.
A Continuous Delivery pipeline is a (mostly) automated software tool chain that takes delivered code, builds it, tests it, and deploys it. This simple concept gets complicated by tool chain realities: no one vendor does everything that needs to be done in the pipeline, and new solutions are evolving every day.
To make sense of the CD pipeline tool chain, I have taken a close look at the market and have identified a set of tool categories. I'm sure I've missed something, and you may not agree with my categories, and in either case I would like to hear from you! You can either comment on this blog, reach me on twitter (@ksbittner), or email me (firstname.lastname@example.org). If you think the categories sound right, I'd like to hear that, too. This is your chance to help define the continuous delivery tools market.
Continuous Delivery Tools & Technologies
Continuous Delivery is a process by which source code is built, deployed to testing environments, test, and optionally deployed to production environment using a highly automated pipeline. Many different kinds of tools need to be brought together to automate this process. The tool categories described below provide the building blocks of the automated Continuous Delivery process.
The modern business world echoes with the sound of time-tested business models being shattered by digital upstarts, while the rate of disruption is accelerating. Organizations that will win in this world must hone their ability to deliver high-value experiences, based on high quality software with very short refresh cycles. Customers are driving this shift; every experience raises their expectations and their choices are no longer limited. Like trust, loyalty takes years to build and only a moment to lose. The threat is existential: Organizations need to drive innovation and disrupt their competitors or they will cease to exist.
I had the good fortune of moderating a panel on the state of digital business at the Chief Digital Officer Global Forum in Singapore yesterday morning. The event showcased a who’s who of digital business leadership in the region, including my panelists Veena Ramesh of Johnson & Johnson, Jerry Blanton of Citi, and Veronique Meffert of Great Eastern Life.
Organizational issues are the greatest hurdle. There was not a single dissenting voice on the fact that organizational challenges represent the biggest impediment to digital business progress. The greatest organizational challenges are functional silos, business unit resistance, a lack of clear guidance from the CEO, rigid backward-looking mindsets, and a shortage of the skills needed to drive change. One approach — shared by Rahul Welde of Unilever — is to drive “digital experimentation funds” and “foundries” to drive co-creation innovation.
Media command centers are becoming critical marketing assets. Both representatives from Unilever and Philips spoke of the critical role that media command centers now play in their marketing campaigns. In the case of Philips, I was surprised to learn that its social media command center in Singapore employs 200 people — and that it is planning for expansion!
Unified information architecture, data governance, and standard enterprise BI platforms are all but a journey via a long and winding road. Even if one deploys the "latest and greatest" BI tools and best practices, the organization may not be getting any closer to the light at the end of the tunnel because:
Technology-driven enterprise BI is scalable but not agile. For the last decade, top down data governance, centralization of BI support on standardized infrastructure, scalability, robustness, support for mission critical applications, minimizing operational risk, and drive toward absolute single version of the truth — the good of enterprise BI — were the strategies that allowed organizations to reap multiple business benefits. However, today's business outlook is much different and one cannot pretend to put new wine into old wine skins. If these were the only best practices, why is it that Forrester research constantly finds that homegrown or shadow BI applications by far outstrip applications created on enterprise BI platforms? Our research often uncovers that — here's where the bad part comes in — enterprise BI environments are complex, inflexible, and slow to react and, therefore, are largely ineffective in the age of the customer. More specifically, our clients cite that the their enterprise BI applications do not have all of the data they need, do not have the right data models to support all of the latest use cases, take too long, and are too complex to use. These are just some of the reasons Forrester's latest survey indicated that approximately 63% of business decision-makers are using an equal amount or more of homegrown versus enterprise BI applications. And an astonishingly miniscule 2% of business decision-makers reported using solely enterprise BI applications.