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5 DevOps Trends that Demand Your Attention

5 DevOps Trends that Demand Your Attention

One of the great things about my job is that I get to go-to software developer conferences all over the world and listen to people being extremely smart. When you watch enough smart talks, read enough articles, and talk to enough people trying to get stuff done on the ground, it gets easier to spot trends—just like it’s easier to see irrigation patterns from the air than from the ground.

Here are the five trends I think you should watch for in 2020.

1. Continuous Integration and Continuous Deployment, but not Continuous Release

I was just at DeliveryConf (which was great and you should try to go next year, but in the meantime, here is a link to the talks ). At the conference, companies of all sizes and maturity levels described how they were working toward the CI/CD goal of getting code into production more quickly. The hesitation we were all feeling our way around was that we want continuous deployment to production, but most consumer and B2B businesses don’t want to change the user experience that often. Simply put, we don’t want Continuous Release.

In fact, customers frequently resent change, especially when it forces them to retrain users in a new workflow. The thing a user knew how to do automatically is now moved or missing, or there is some new option that no one knows how to use effectively. Interface changes in popular software can mean that companies spend millions of dollars in retraining. Anything that interrupts a user’s unconscious competence and forces them to think about what they’re doing slows them down.

Release is a business decision, and it often is safer and cheaper and better for users if all the changes come at once, so they can all be discussed and taught at the same time. CI/CD, on the other hand, is a technical choice. But that doesn’t mean customers need to experience that cadence, as long as you can deploy without releasing.

2. Leveraging existing workflows

Similarly, there is no reason users should have to learn new workflows just because the tools their software group is using have changed. I think this year, we’ll see a lot of SaaS vendors work with existing enterprise tools to make those tools more powerful, without changing the user experience much, if at all.

I think of this as leverage. It doesn’t matter to a user if a form is backed by a spreadsheet that needs to be manually imported or if it’s wired directly to a CRM. The user has applied the same amount of effort, but the new tooling has moved the fulcrum point, and the user’s work is more effective.

3. Personalization

We don’t all want the same things, as we can tell from the Dark Mode Wars. As our bandwidth and information have changed, so have our expectations about how much we can make our technology spaces personally comfortable.

A great example of this is the Google Now app on Android phones. You can tell it what sports team you follow, and then the app will deliver more news about that team and sport. But it also gives you the option to hide gameday spoilers if you’re not going to be able to watch it right away. They aren’t hiding that information from everyone, or even fans of that team, but they are personalizing the experience by protecting you from knowing the score of the game before watching it.

Personalization gives users more control over their experiences. It also provides more options than would otherwise be feasible to present globally. We can’t be all things to all people, unless we allow people to choose which subset of all things they want, and then allow those subsets.

4. Accessibility

The other exciting possibility of increased personalization is better support for different accessibility needs. The US has had web accessibility standards since 2000, but they haven’t been enforced or adopted evenly. That said, we have seen some recent exceptions.

The Supreme Court just ruled against Dominos in a lawsuit alleging that the pizza company failed to comply with accessibility standards. I’m not going to say “this changes everything”, but I will say this might be a good time to be an accessibility consultant who can help teams retool quickly.

The interesting part, and the thing that meshes with personalization, is that different people can have different accessibility needs. Someone with low vision needs solutions that may be incompatible with tab-based navigation, which again may be hard to align with screen readers. Rather than trying to make a single “accessible” page that meets none of those needs well, we’ll use personalization to tune for exactly what different people need.

5. Scientific thinking

This is an interesting outflow of our emphasis on data and metrics. Now that we are doing a better job of democratizing access to statistics and metrics, it’s easier for everyone in the company to understand how changes affect user behavior. Rapid releases and Progressive Delivery make it much easier for us to see how our choices work out in near-real-time. That means it’s possible for anyone—not just the UX team—to see how changes play out. With that visibility, we also can form a hypothesis about how a change will affect the data and then look to confirm or reject the hypothesis.

The scientific method is not heavily taught in most computer science programs, because it wasn’t until recently that we had the fast feedback loop that would make it useful. However, at least in the US, most schoolchildren are taught the basics in elementary school. They learn to ask critical questions like:

-What is the current state of the system?

-What change am I making?

-How can I measure a change’s impact?

-Was the impact what I expected it would be?

-Do I have any evidence for why or why not?

We need to be able to ask these questions at the team and individual level and get meaningful answers. We can then use those answers to iterate rapidly and stay attuned to what users want and find useful. What’s more, we can avoid spending months building things that virtually no one needs or wants.

What do you see coming in 2020? How will this play out in your company or industry?

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Heidi Waterhouse is a developer advocate at LaunchDarkly. She is working in the intersection of risk, usability, and happy deployments. Her passions include documentation, clear concepts, and skirts with pockets. As a developer advocate, Heidi bridges the experiences of external and internal developers and spends time listening, thinking, and learning deeply about the business and technical challenges that face each group.

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5 Tech Trends That Businesses Can’t Afford To Ignore

With technology evolving at such a rapid pace, some business owners are left digitally disoriented as they try to figure out which of the latest innovations they need to invest in and what they can ignore.

It can make for confusing times.

All that bewilderment aside, though, these fast-developing advances also create opportunities that can help small and medium-sized businesses become more competitive – if they understand how to seize them.

“Technology exists today that at one time was available only to large corporations with huge technology budgets,” says Chris Hoose (www.choosenetworks.com), an IT consultant who works with small businesses.

“Every year, technology becomes even more accessible to companies of all sizes.”

Hoose says businesses that want to stay on top of their games should make sure they invest in these technological trends, if they haven’t already:

The Internet of Things. Many Internet of Things-connected devices, such as smart refrigerators and thermostats, are designed for home use, but there are also applications for small businesses, Hoose says. Some examples: smart locks use digital keys that can’t be lost or stolen, and log a record of who uses a door and when; RFID tags on merchandise can prevent theft and automatically update inventory; and mobile-card readers can replace cash registers.

Artificial intelligence. Don’t be fooled into thinking that AI is something only the big organizations can afford to use, Hoose says. “It’s making inroads into technologies accessible for businesses of all sizes,” he says. “AI can help you offer increasingly personalized experiences to customers by maximizing your time and automating manual tasks, like data entry.” AI also can be used to improve decision making, Hoose says. Essentially, AI will help you take that jumble of data most businesses have and analyze it in a way that allows you to make better-informed judgments on the actions you need to take.

Telecommuting. The office world is changing and more workers spend at least a portion of their work week telecommuting. “In many cases remote employees use their own equipment, which can eliminate some of the company’s costs with purchasing and maintaining computers, printers and mobile phones,” Hoose says. Video conferencing, instant messaging and other advances are helping to make telecommuting a viable option, he says.

Customer-relationship-management (CRM) software. Any application that a business uses to interact with customers, analyze data, or recommend products and services to customers is “part of the CRM family,” Hoose says. “This type of software helps your team manage, control and build customer relationships,” he says. “It can log your team’s touchpoints with prospects, including emails, phone calls, voicemails and in-person meetings. You can have a complete record of your team’s interaction with a prospect that’s easy for anyone to access.”

Voice search. Consumers increasingly are making use of such AI assistants as Siri or Alexa to help them do internet searches using their voices. “Voice search is changing the way people find information because these queries are structured differently than when we type terms into a search engine,” Hoose says.

“Organizations of all types can benefit from optimizing their content to improve where they fall in a voice search.”

“To help propel your business going forward, it’s important to stay abreast of technology innovation,” Hoose says. “These technologies will help you expand your customer base, create more efficient in-house processes, and increase engagement from both customers and staff.”

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Chris Hoose (www.choosenetworks.com) is the president of Choose Networks, an IT consulting firm for small businesses. Hoose started the company in 2001 to give large-scale solutions and support to businesses that can’t afford their own in-house IT department. He earned a Master of Information Systems Management from Friends University.

The Logistics of Data Quality for Your Marketing and Sales Initiatives

Global Trade recently highlighted an annual 3PL trend study that indicates one of the biggest goals for logistics companies in 2019 is to prioritize customer relationships.

Developing strong customer relationships relies on effective customer engagement and communications. Most logistics companies are familiar with the technology and tools that help them manage fleets, track inventory, and improve operations. But, a growing number are leveraging customer relationship management (CRM) technology to improve customer engagement and support sales and marketing initiatives. The timing couldn’t be better, because if prioritizing customer relationships is a key focus in 2019, prioritizing the data quality in CRMs is an essential part of the mix.

The Impact of Data Quality

To prioritize CRM data quality, the ultimate goal is a CRM database free of duplicate records, missing or wrong details, and non-standardized entries (e.g., entering Corporation when Corp is preferred). But bad data is added to the system through list imports, manual entry, and typos on web forms when data quality tools aren’t in place to catch duplicate information or invalid data. In the absence of data cleansing routines, even good data begins to decay as contact information changes and companies merge or close.

Without a data management protocol in place, it is impossible to realize the full potential of CRM data to guide business activities. In the case of the logistics industry, muddying reports with user data errors leads to misdirected marketing and sales growth efforts. This can create frustrating interactions with the company, poor customer experiences, acquisition and retention challenges, and ultimately, lost revenue.

The High Cost of Bad Data

The logistics industry is no stranger to the importance of maintenance. Left unchecked, a small problem with a fleet can become a big problem with domino effects that bottleneck the entire supply chain. There’s a similar impact with a lack of data maintenance.

According to the 1-10-100 quality principle, the relative cost of fixing a problem increases exponentially over time. So if the cost of preventing bad data from entering the CRM is $1, then the cost of correcting existing problems is $10, and the cost of fixing a problem after it causes a failure is $100. The issues and costs are compounded as that bad data begins to pollute marketing and sales initiatives, decreasing campaign ROI and reducing customer engagement.

The Two-Step Data Cleansing Process

To stop the cycle, a cyclical approach to data quality and maintenance is needed. The following two-step data cleansing process is a great place to start.

Prevention is the first step. The company must ensure those who use the CRM system leverage best practices for entering and updating data without introducing errors. Examples of clean data best practices include completing all data entry fields required for a record, following a standard naming convention, checking for duplicate records before entering new information, and ensuring the validity and deliverability of email addresses. It’s also wise to consider creating a data governance policy that formalizes these practices and embeds data quality in the company culture.

Remediation is the second step. This involves keeping data accurate with regular data cleansing routines that include steps to remove or merge duplicates, standardize content, and verify email addresses. It should also include checking data against credible outside sources occasionally to determine if it’s up-to-date or stale.

With either step, some areas of data quality and entry are challenging even for the most detail-oriented data users or administrators. This makes the availability of third-party data quality tools that go beyond the native functionality of CRMs an important option. Companies can choose solutions that are compatible with their CRM and should look for those that are particularly effective at supporting data integrity during mass imports, streamlining and automating data quality processes, and customizing how duplicate records are managed. Email verification tools can also be leveraged to verify the email addresses in lists before importing them, directly in Salesforce to support lead follow-up, and at the point of capture (for example, adding an API to web lead forms to verify email addresses as they are entered).

Data Quality Is Logical

There’s a growing trend in viewing quality data as a high-value business asset. Studies show senior leadership is increasingly acknowledging the need to support data quality and 85 percent of corporations indicate they are trying to incorporate data into their business strategies. Likewise, the value of using CRM data to get to know customers better and improve customer experiences is widely recognized.

To achieve significant growth in their customer base and revenue, it’s time for logistics companies to give importance to marketing and sales data the way they’ve given importance to distribution, warehousing, and fleet data. People and human-error, not technology, hold data back. As noted in an article from Salesforce.com, “The value of CRM isn’t in the product; it’s how you use it.”

Implementing a data management protocol is the only way to navigate human error and get the most value from the CRM. The resulting higher quality data will bolster marketing and sales activities, and help logistics companies better understand, reach, engage, and retain their customers. Once the previously mentioned two-step process is in place, companies can revise and refine data quality processes as they learn more about what clean data means and how to deliver great customer experiences using quality CRM data.

Ashley Sierant is a data quality management expert, overseeing successful implementation of Validity tools for clients. Validity is a leading global provider of data integrity and compliance offerings that tens of thousands of organizations worldwide rely on to trust their data.