DevOps is one of the most powerful weapons that CIOs have in their arsenal. DevOps unites the entire enterprise in delivering business transformation with superior customer experience. Companies like Target, Capital One, Walmart, ING, Nordstrom, Netflix and JetBlue are already reaping the benefits. In order to unlock the promise of DevOps, CIOs must lead the call for cultural change.
As any leader knows, changing institutionalized behavior is the toughest of all management challenges and CIOs are understandably skeptical of new trends. Despite this, CIOs must recognize when a trend becomes an imperative for survival. DevOps has become this imperative, and CIOs must act now. CIOs who embrace the DevOps challenge must first fostera culture of collaboration and learning, then enable their people with the right tools to drive holistic life-cycle automation. Those who meet this challenge won't just beat their competitors — they will decimate them.
CIOs must replace traditional linear thinking with Agile thinking.
Customers hold the power in their relationships with businesses. Today, it's not enough for businesses to deliver products. Customers expect them to deliver outcomes and success.
To do this, businesses must understand who the customer is, what their pain points are in achieving their business goals, and must help them choose the right products to meet their goals. The relationship does not stop there. Businesses must ensure that a new customer is properly onboarded, and is realizing ongoing value from their purchase. Forrester data backs these statements up. 68% want vendors who “understand my business, my problems – and help me solve them.”
This is the mission of customer success teams. They actively manage customers post-purchase, to ensure their ongoing success, with the end goal of reducing churn, increasing customer lifetime value and advocacy - the latter of which influences new sales.
Most businesses pursue this mission by standing up customer success organizations. They use a health score — comprised of financial data, CRM data, product usage data, support cases, customer feedback — to track their customers. However, most company employees interacting with customers don’t have this visibility into a customer’s health which can impact overall relationships.
Totango, a vendor of customer success solutions, has a very different view of customer success. Sure customer success teams manage overall customer relationships. However, Totango believes that everyone interacting with customers must have access to customer data and their health in order to better engage with them. Employees must also be able easily, with little friction, access this information from within the context of their application.
To be blunt, if you miss this event, you’ll be sorry. Sure there are loads of marketing conferences out there, but Forrester’s Forums clear the clutter and help you focus on the issues that matter most to your success. Last year, we told you that we're in a post-digital world now, and that marketing must adapt to new rules. This year, on April 5-7, we'll show you exactly how to do that and more. Whether you’re developing and refining your marketing strategy to engage today’s empowered consumer, or your planning the next investment in your Martech application portfolio, Forrester’s Consumer Marketing Forum will be the smartest investment of time that you’ll make this year. Here’s a just few highlights:
Learn exactly how consumers’ behaviors are changing. Analyst Anjali Lai will share Forrester's Empowered Customer segmentation.
Discover how to avoid the illusion of insights. VP and Research Director Sri Sridharan will show you how to avoid potential pitalls in your question to become and insights-driven business.
Reveal what really matters in Martech and Adtech. VP and Principal Analyst Joe Stanhope will bring clarity to the chaos of an unhealthy technology ecosystem.
If you already belong to a high-performing DevOps organization and you are working on leveraging opensource for monitoring to drive feedback loops, or delivering better security with DevSecOps, or making sure you are understanding continuous testing then you don’t need to read the following – you can stop now.
However, if you are facing the challenges that your app dev team is developing faster than you can deliver or you realize that ITIL does not help you in increasing your speed and quality of deployment or your manual deployment capability do not scale or human error has caused some outage…don’t delay your shift your operating model towards DevOps. Our DevOps vision report gives I&O leader’s guidance on how to modify the operating model to focus on velocity and quality to deliver “great” customer experiences.
Products not functional silo’s for customer obesession
The first transition is one of focusing on products not functional IT silos. Developers, operations, QA teams and release teams should be merged into a single team around the product. This team is accountable for the complete pipeline from ideation to delivery and depending on the culture, support as well.
Evaluate your success, based on the five critical DevOps metrics.
We spoke to 20 sales enablement practitioners from a variety of industries who were evenly divided between reporting to marketing and sales. That is a lesson on how the role of sales enablement still straddles the organizational divide. And as with any technology, it takes a lot more than flipping a switch for SEA systems to get up and running. All practitioners agreed that getting their house in order (that is, finding, categorizing, reviewing, and restructuring content) was a necessary first step no matter what solution they chose.
The most immediate measure of a successful launch and implementation was adoption by sellers. “They love it! Content is much easier to locate,” was a frequent comment. But beyond immediate adoption, there are still challenges for many sales and marketing leaders in getting the most out of SEA, including going beyond using basic content usage reporting to correlating successful content with moving opportunities through sales stages.
The new data economy isn’t about data; it is about insights. How can I increase the availability of my locomotive fleet? How can I extend the longevity of my new tires? How can I improve my on-time-in-full rate? Which subscribers are most likely to churn in the near future? Where is the best location to build a new restaurant franchise or open a new retail outlet? Business decision-makers want answers to these kinds of questions, and new insights services providers are eager to help them.
A growing number of companies recognize the opportunity their data provides, and they take that data to market: 1/3 of firms report commercializing data or sharing it for revenue with partners or customers. The recently published Forrester Report Top Performers Commercialize Data Through Insights Services discusses the new trends in data commercialization: who is buying, who is selling, and what offerings are available, from direct data sales to the delivery of data-derived insight services.
While some commercializers avail themselves of data markets such as Dawex or DataStreamX, many are creating more sophisticated data-derived products and services. They are becoming insights services providers, often as an incremental offering to their existing customers. Some offer insights based on smart products and IoT analytics. Siemens Mobility, Boeing, and GM offer predictive maintenance for their planes, trains, and automobiles. In the agricultural products industry, companies such as Monsanto and DuPont offer services that prescribe when and what farmers should plant, when certain interventions, such as water or pesticide applications, are advisable, or when to harvest.
Every year we run a staffing and hiring survey of what used to be “eBusiness” professionals. I say “used to” because increasingly we find that eBusiness teams have morphed into “Digital Business” teams. Why? Well teams are under an increasing set of pressures, including:
A mandate to drive strategic change throughout the organization. Seventy two percent of firms surveyed are executing on digital transformation, and that tables the topic of digital with the C-Suite. Digital business leaders now have more strategic responsibility and must wield stronger influence with their executive peers and leaders.
In 2016, we learned a lot about how complicated it is to gather and interpret data that will help brands uncover people's motivations, interests and behaviors. At Consumer Marketing in NYC next month, we'll be taking these topics head-on, trying to understand how far data can go to helping us understand and target the right people at the right time.
One of our guests who I'm most excited to hear from on this topic is Danielle Lee, Global VP, Partner Solutions at Spotify. I had a chance to chat with her about some of her thoughts around deterministic targeting and music-based insights. Here's what she had to say:
How do you define "people-based marketing" and why do you think it will become the gold-standard?
People-based marketing represents an industry shift from targeting devices to connecting with the right people at the right time, with the right message. Rather than targeting ads to devices based on cookies, which is fraught with inadequacies, marketers can now reach people across the many devices they use, thanks to persistent identity.
The reason we’re so excited about it at Spotify, and the reason we think it will become the gold standard for marketing, is because it works. With people-based marketing, you have greater assurance that your message is reaching your known customer and driving measurable results.
Mobile World Congress (MWC) which took place in Barcelona once again broke new records in terms of attendees, reaching 108,000. Yet, discussions with end-user businesses indicate that mobility is often no longer treated as a standalone focus area by CIOs and CTOs. Mobility has become part of the broader digital transformation initiative. This has implications for mobile strategies. It also affects the decision where a business leader turns to in order to find inspirations for her digital transformation initiative.
Of course, mobility remains a critically important building block for all digital transformation initiatives. But mobility is part of a wider technology-driven business transformation. In my view, the biggest themes at MWC in 2017 that are relevant for digital transformation relate to IoT, AI, platforms, collaboration, and connectivity. I discuss what these themes mean for the CIO in a separate blog.
Importantly, all of these themes are interwoven. Hence, the CIO needs to build her digital transformation strategy on a comprehensive approach - with mobility is right at the heart. Still, there remains a risk that the CIO gets sucked into pursuing a compartmentalized technology strategy that lacks a comprehensive view of the real business objectives. It is essential that the CIO avoids a ‘bolt-on approach’ to these technology investments because of the technology interdependencies.
Yogi Berra once said, "It's tough to make predictions, especially about the future." It is tough indeed, but enterprises that can make probabilistic predictions about customers, business processes, and operations will have an edge over enterprises that can't. These predictions don't have to be macroscopic to be consequential. Predictions about what a customer is likely to buy next. Predictions about marketing content that will resonate with a prospect. Predictions about the next best action to take in a business process. Predictions about when an expensive asset is likely to break down. Virtually any customer journey, business process, and even strategic decision can be made better if permeated with the power to predict.
Predictive Analytics And Machine Learning Solutions Make It Possible
Yes, making accurate predictions is tough, but predictive analytics and machine learning (PAML) solutions provide data scientists and developers alike with the tools to make it happen. Forrester defines PAML solutions as:
Software that provides data scientists with 1) tools to build predictive models using statistical and machine learning algorithms and 2) a platform to deploy and manage predictive production models.
The Forrester Wave™: Predictive Analytics And Machine Learning Solutions, Q1 2017