Getting the CMO Onboard with Agile Marketing Practices

In my last post, I shared 5 Reasons Why Marketing Organizations Must be Driving Digital and in this post, I'm following up on agile marketing.

Agile Marketing
Many of the marketing departments I've worked with are in fact practicing some form of ad hoc agile. In some cases, timelines are fixed, like when the marketing department is hosting an event or when there is a holiday driven promotion. Other times, they are given jobs to do based on organizational needs like updating sales materials, content marketing related work, or updating the website. Other times the work is more recurring like getting the monthly newsletters published or nurturing leads. Finally, there are strategic initiatives such as updating brading, developing go-to-market strategies for new products, or leading market research initiatives.

All of these activities can be managed in a scrum process. IMHO, many marketing teams would welcome this structure and often the main things missing is the endorsement from senior leadership (the CMO) and agile tools for managing their workflow.

Tools can be addressed if the CIO or CTO already practice agile in IT, and this is a good place for CIO and CMO to partner. The question is whether marketers will be open to using the same tools because many agile tools are oriented toward software development. Jira for example uses terms like "releases", "versions" and "components" that can be adopted to marketing needs but require marketers to be open minded. So for example, releases are essentially milestones and components can be marketing assets.

The CMO wants Agile to Drive Better Decisions


But the main barrier for marketing organizations adopting agile may be the CMO. Agile helps teams collaborate and have a voice on what's achievable in a fixed amount of time. In scrum, this is done each sprint and through the commitment meeting. But CMO who have specific quality requirements, timelines, and a fixed idea of what needs to be delivered will have a hard time accepting a marketing team's commitment to something below these expectations.

But I have yet to meet a CMO with such rigid expectations. Most executives want to understand tradeoffs and will make reasonable decisions on priorities when confronted with options. Agile marketing is a practice to get there. Just like in technology, marketing teams can present different solutions with different story point estimates to enable a discussion on options and drive decisions.

If your marketing is practicing agile or wants to, I'm very interested in hearing from you! Contact me @nyike or on linkedin.


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5 Reasons Why Marketing Organizations Must be Driving Digital

Why marketing organizations are transforming their organizations with driving digital practices



Driving Digital Sacolick
Last week I had the privilege of speaking at KintoneConnect on Driving Digital: Key Practices to Lead a Smarter and Faster Transformation. The talk included some key concepts from my book, Driving Digital: The Leader's Guide to Business Transformation Through Technology on why digital impacts most businesses, how agile planning practices drive transformation, and how organizations can increase their digital capabilities with citizen data science and lowcode development programs.

The fun thing about this talk was that it was largely to a non-technical, non-executive audience who were very eager to learn about how to leverage digital practices to drive business transformation. It reminded me of a recent post, 3 questions from employees on digital transformation and how to answer them based on another recent talk on the sacrifices executives and employees need to make to drive a digital transformation.

Applying Driving Digital Practices in Marketing.


Why Marketing? In some ways, the marketing department has undergone similar strategic, practice, technology, and skill transformations as IT departments over the last several years.

  • In technology, many companies are adopting the practices of software development companies in order to compete in a digital world. Similarly, many marketing organizations are developing comparable digital marketing practices to B2C companies including developing digital brands, positioning products and running omnichannel marketing programs.

  • Marketing today is largely driven by a set of experiments aiming to reach prospects and customers with a call to action. Many are adopting agile marketing practices that enable them to develop experiments aligned with strategy, prioritize a backlog, and execute marketing programs similar to how technology organizations leverage agile development practices.

  • Marketing departments must be extremely data driven in order to identify customer segments, align messaging, and optimize channel experiences. 

  • Similar to technology organizations, marketing teams are often one organizational function removed from the direct sales and support of customers. But in today's digital world, both marketing and technology organizations are being given digital charters to drive customer experiences and grow revenue.

  • Also like technology organizations, it's important for marketing organizations to drive efficiencies through automation and to leverage a toolbox of cloud and SaaS tools to enable new capabilities. 

Of course, many marketing organizations have been investing in digital marketing capabilities and marketing automation platforms for some time. In fact,  I called upon CIOs to help CMOs with posts three years ago on helping with marketing automation, on enabling the data driven marketing organization, and on partnering around technology selections.

But like technology organizations, marketing teams have to be driving digital, smarter and faster in order to get their brands and products to market. I'll share some more details on how marketing departments can adopt agile, data, and other driving digital practices over my next few posts.

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Lowcode Platforms are Key to Digital Transformation

Forrester recognizes two lowcode platform types, one targeting business users and the other for application developers.



Java, .Net, PHP, Javascript, Ruby,  and Python along with the very large number of MVC and other frameworks that support these languages are appropriate tools when you need to develop an application that requires complete control.

But for many applications, the MVP can be developed on platforms and with tools that enable rapid development. I've been writing about lowcode, citizen development platforms and feature this in my book, Driving Digital: The Leader's Guide to Business Transformation Through Technology.

Now Forrester has published two Waves, one for lowcode platforms that target business developers (ie, citizen development platforms) and a second for application developers. They place Quick Base, Caspio, and MatsSoft at the top for business users with Kintone, FileMaker, Microsoft and Nintex as contenders. For application developers, Outsystems, Mendix, Appian, Kony, and Salesforce are at the top with ServiceNow, AgilePoint, and K2 as contenders.

What lowcode platforms enable


I myself have developed a good number of applications  on lowcode platforms including enterprise tools for portfolio management, hiring/interviewing, and IT budgeting.

Many of the business platforms aim to enable business users to develop workflows and knowledgebases that work better than spreadsheets and email while providing richer collaborative experiences than messaging applications. They enable the development of web and mobile user interfaces that have both workflow and collaboration capabilities.

The lowcode development platforms often include capabilities to integrate with other enterprise systems, databases, and APIs. They often enable developing an experience that can be optimized for phone, tablet, and web. These lowcode platforms also tend to have application lifecycle capabilities so that applications can be developed and tested outside of production environments.

Why lowcode platforms are needed by most businesses


As I discuss in Driving Digital, these platforms should be part of every CIO's digital transformation agenda. If you're going to enable the workforce to work smarter and faster, then it requires developing digital tools targeted to each department's need. For example. sales, marketing, operations, and financial teams all have different needs when accessing ERP, CRM, and marketing systems. If application development is easy and economical then developing experiences that target the end users' needs likely increases utilization and improves productivity.

In addition, workflows developed by sharing spreadsheets or emailing other office documents is error prone and can be less productive. Many of these lowcode platforms are used to develop applications where ones never existed, or can be used to phase out workflows on old legacy systems.

So if the IT department is overwhelmed, if your organization is inundated with manual or email driven processes, or if you are looking at too many point SaaS solutions for limited-need workflows, then instrumenting a lowcode platform may be a sound investment. 
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How Digital CIOs Manage Their Time

Earlier this year I published the post, What discipline should CIO master to drive transformation, where I highlighted the importance of time management skills CIOs must master when leading digital transformation programs

In this post I expand the analysis to show two other operating scenarios and illustrate each priority based on its impact on growth versus running the business.

The CIO Leading Transformation

The scenario I highlighted in the original post is shown below and provides more detail. While running transformation programs, CIOs get more involved in engaging customers, developing products, application development, aligning senior leadership, and data and analytics programs.

Digital CIO Time Management Leading Transformation

The CIO During Strategic Planning

During the budget season and strategic planning periods, many CIO shift gears and priorities. They are more likely to be working with the C-Suite and general managers on business plans, preparing for Board presentations, engaging sales and marketing on their needs, and working with their analytics teams to ensure decisions are data driven. They are also likely to be working with their PMOs and technology leads to plan out the next year's initiatives and investments.


The CIO in Crisis Management

When there is a major business issue or crisis, the CIO is more likely to be working with their Operational and Security teams, followed by the non-tech and tech staff that are tied to the issue. They will engage the C-Suite to keep them informed on the issue and current status. They will also work with Sales and Marketing leads to make sure the appropriate communications are sent to customers.

Digital CIO Time Management Crisis Management

CIOs and Their Leadership Staff

Unfortunately the real world is more complicated as different businesses have conflicting needs. A CIO might be working with one business unit to plan a major growth initiative while at the same time be fighting a crisis for a second unit.

This is where a CIOs have to communicate with their lieutenants. They should be clear on their focus and where they need their lieutenants to step in and take ownership. Sometimes that means delegating strategic work to lieutenants and other times, having a lieutenant fully manage a crisis.

And that's how CIOs get more done - and how lieutenants learn to become CIOs.

Feel free to review the full CIO Time Management Dashboard.

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3 Signs You Have Overloaded Your Digital Transformation Program


Pressure to take on too many initiatives may bottleneck the overall program and burnout participants




I am an advocate for speed and doing more. I’ve seen products, businesses, and an entire business models fall off the cliff because executives were too slow to respond, experiment, invest, challenge sacred cows, and scale toward new digital business models. So, when presented with the opportunity to lead transformation programs, I would rather say yes to new initiatives especially when they deliver improved customer experiences, grow revenue, improve analytics, or are likely to replace an existing legacy revenue stream.

I often get asked, “How much is too much” and its corollary question, “Can the team take on one more important initiative?” The core of these questions is whether you are pushing leaders and the team too hard and overloading them with too many initiatives.

I have a method that helps address these questions outlined in my book, Driving Digital: The Leader’s Guide to Business Transformation Through Technology. It involves understanding how to effectively plan projects, what type of team structure enables you to scale and add people when required, and how to manage the impact to end users (both customers and employees) as the initiative delivers changes. It would require too much detail to share in a blog post.

But what I can provide are some of the symptoms and indicators of when an organization, a team, or a person is overloaded. My focus is at an organizational level, but since people have different productivity levels and abilities to handle stress you also should consider the impact on individuals. For this, review other articles to help individuals such as signs that employees are suffering from stress and helping a coworker that is stressed out.

Signs of Overload


So here are signs that you can observe and even measure at the organizational level indicating that the team may be overloaded  

1. Lots of great ideas, few are being implemented 

This can happen for a few different reasons especially if you don’t have a defined process to plan initiatives or if your innovators are on the hook to plan too many of them. This is a problem that’s easy to measure and harder to solve. Start by looking at who is leading or has a significant role in each of your initiatives and you are likely to find several innovators assigned to too many programs. Everyone has their limits on how much multitasking they can handle and how much they can get pulled in different directions. Even with some simple guidelines, your initiative to resource mapping should give you clues where you have taxed key people.

You will also find initiatives that are under resourced and making progress at a glacial pace. You can use this resource and initiative mapping and if an initiative is under resourced at the leadership level then it's less likely to make consistent progress.

2. You are spending more time communicating than getting things done 

The more independent things you are trying to plan and execute on, the more communications are required. If you feel like key members of the team are spending a lot of time and energy getting on the same page, aligning on priorities, achieving consensus on solutions, or reporting on status then it’s likely that they are overloaded. Collaboration tools can improve the productivity around communications, but if innovators are context switching too much then it's difficult for them to get the things they committed to done.

3. Users are slow to adopt, and many are not happy 

Changing workflows, behaviors, mindset, and culture often happens over longer timescales than the time it takes to introduce new capabilities. If you're introducing new capabilities to multiple organizations such as sales, marketing, and operations then you must schedule them around their peak periods of activity and gauge how much change they can manage. Transformation programs often require leaders to push organizations to learn and adopt new practices quickly, but pushing too hard can easily overwhelm a group.

How you handle this depends on many factors. Most important is too identify key people in these organizations from leaders down to entry level employees that are "early adopters" of new capabilities, are in tune with their organization's pulse, and are prepared to give you honest feedback. Since they are early adopters, they are likely to give you practical feedback on the capability you are introducing. If they are equally in tune with their organization, then they will balance this out with insights on the success and roadblocks getting mainstream adoption across the organization.

Leaders Must Drive the Urgency

If you're trying to move your organization smarter and faster, then employees must hear this message repetitively. More specifically, they must understand why the urgency and how going too slow impacts customers, employees, and them.



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5 Steps to Prepare Your Organization for Artificial Intelligence

Last week I delivered a keynote talk at Synechron's InSync Charlotte event around developing the data driven organization. The talk showed the audience the alignment between digital transformation and data driven practices and how evolving data practices should address small data (through citizen data science programs) and big data governance that can enable organizations to be organizationally ready to experiment with machine learning and artificial intelligence. Later that evening, I shared the stage with Imam Hoque, COO of Quantexa and Sandeep Kumar, Head of Capital Market Solutions at Synechron where we answered questions about AI in the organization.

McKinsey Global Institute -
Artificial Intelligence
The Next Digital Frontier
Let me share a punchline from a recent WSJ article, Artificial Intelligence Is Ready for Business, Are Businesses Ready for AI?
The report is based on a survey of over 3,000 AI-aware C-level executives across 10 countries and 14 sectors. Only 20% of respondents had adopted AI at scale in a core part of their business. 40% were partial adopters or experimenters, while another 40 percent were essentially contemplators.
So unless you work for a tech company, it's very likely that your AI journey is just beginning if it has begun at all. The main barriers fall into three categories (i) lack of talent, (ii) data isn't ready for AI, and (iii) unclear to business leaders what problems and opportunities where AI can drive value.

Preparing for AI 


So if you are an experimenter or a contemplator, what are some steps your organization should consider to be ready to leverage AI? Here are my five - 
  1. Define data governance - This may seem like an odd place to start, but without a data governance policy stating who has access to data and on permissible uses it can lead to organization dysfunction. Some will interpret the lack of a data policy to imply that they can do anything they want with the available data, others will be paralyzed and may prevent basic data from being used in analysis. Data governance teams should also be developing data catalogs, dictionaries, and reviews of data quality that are all important for using data in AI experiments. 

  2. Establish your data lake - AI and ML algorithms work best when lots of raw data is applied to them. Centralizing primary data sources (including external ones) makes it easier for AI developers and data scientists to tap in and leverage them. In Chapter 3 of my recently published book, Driving Digital: The Leader's Guide to Digital Transformation Through Technology I cover the data technologies many organizations use to develop nosql data stores and other data lakes.

  3. Find industry partners - AI talent is still scarce, and leveraging AI to develop insights and applications may be a long journey for many organizations that cannot attract sufficient talent. In addition, AI applications can be developed to leverage industry knowledge and plug in common data sources. For these reasons, many organizations will benefit by partnering with AI experts in their industry rather than building on their own.

  4. Identify examples out of your industry - Many business leaders are still learning about what types of problems can be solved with AI. While you might find some examples in your own industry, you'll get a better sense of the opportunities by looking at successes in other industries that are strong in the AI areas of interest. Looking for AI in customer experience then maybe review retail experiences. Have a lot of unstructured content, then look at news media for examples of natural language processing and natural language generation. Want to use AI to identify fraud then look for Banking and Fintech examples. 

  5. Backlog POCs that drive value - Once you have your data policies in order, a starting data lake, an understanding of where industry partners can help you accelerate, and some basic learning in your organization about where AI is successful then you're ready to explore options in your organizations. Start by asking big, bold questions, consider the value in the result rather than the path to get there and then plan to experiment

These steps shouldn't be done in sequence. Data governance is likely to be an ongoing program while building the data lake, identifying partners, and seeking examples should be parallel activities. Once milestones are achieved in these areas, then you can consider brainstorming POCs.

What are your AI plans for 2018?
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How to Implement Agile on Lowcode and aPaaS Development Platforms

A colleague and friend recently asked me whether agile practices were appropriate when managing development on lowcode or aPaaS (application Platform as a Service) technologies. These higher level languages enable developers to write a class of applications faster and maintain them easier by providing development environments, programming constructs, and other tools. Many of these platforms are designed to rapidly develop mobile applications or applications that connect to disparate data sources. They differ from citizens development platforms and citizen data science platforms which target business end users and enable these user to develop applications, dashboards, and other tools without having to use coding constructs.

How LowCode and aPass Development Differs from Software Development


I reference lowcode development platforms in my book, Driving Digital: The Leader's Guide to Business Transformation Through Technology as a means for enterprises to develop the tools to empower their workforce and to provide capabilities to tailored customer segments. I've used them to develop applications to track the IT budgets, manage a large portfolio of projects, and to establish workflows on hiring and recruiting.

So here are some of the differences between traditional software development and lowcode/aPass development that impact agile practices


PracticeSoftware DevelopmentaPass / LowcodeAgile Impact
RequirementsRequires upfront design and UX with detailed accepted criteria on functionalityDesign, UX, and functionality often bounded by the capabilities of the platformProduct owners must know the capabilities of the lowcode platform to stay in its scope of capabilities, but can often draft more simplified requirements and acceptance criteria
DevelopmentCan scale from small to very large teams. Leverage standards for coding, commenting, and documentationOften designed for individuals or smaller teams. Coding and documentation capabilities differ by platformEnables rapid development around functionality, but documentation may require additional effort outside of the lowcode development platform
TestingDevelopment practice should factor automating unit, functionality, performance and security testing. UAT should focus on user experience UAT focus on functionality and workflow but specialized testing is often required to validate algorithmsMore opportunity to bring business users into the development process to validate implementation while developing
DevOpsDev and Ops teams need to select and implement tools/standards to for continuous integration and deliveryDeployment steps are often factored into the lowcode platform, but platforms may not have the capability to version or rollback a changeLowcode platforms without roll back and versioning capabilities have higher risks when introducing large functionality or workflow changes

Recommendations on Implementing Agile in Lowcode


Based on the factors identified above, here are my recommendations for leveraging agile in lowcode and aPaaS development environments

  • Make sure the application need is appropriate to the platform because trying to use lowcode platforms as a Swiss army knife to every development need can result in applications with poor user experiences and coding complexities.

  • Leverage shorter sprints to take advantage of the rapid development capabilities and fewer testing needs of the platform. For many platforms one-week sprints are possible.

  • Focus story writing on workflow and user experience since the technical implementation is bounded by the platform's capabilities.

  • Challenge requirements that drive customization and software development outside the capabilities of the platform since this drives complexity in supporting the application.

  • Add UAT members to the team so that business user testing can occur while development is in progress and ensure "shippable code" at the end of the sprint.

  • Optimize for shorter release cycles of 1-2 sprints especially if the platform doesn't have versioning or rollback capabilities.

  • Require technical documentation with every release to avoid accumulating technical debt and making it difficult to introduce new developers to support applications.

  • Factor in time to perform and test upgrades so that you don't fall behind in the supported versions of the platform.

One last word. There's significant diversity of lowcode platforms and their technical capabilities, so my recommendations are general guidelines.  


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