Tag Archives: Prioritize
Media Industry Post COVID 19: Prioritize CRM & Customer Data
In the Post COVID-19 Media Industry, Customer Data Management Will Be Essential to Success
There’s no question that COVID-19 has created massive challenges for businesses around the globe. But while some industries are struggling to keep up, others find themselves in an opportune position. The media industry is dealing with both, and better customer data management is the solution.
Providing consumers around the globe with accurate, reliable information is more important than ever before, and media organizations are leading the way. At the same time, however, advertising revenue is down — and this can create revenue challenges for large media companies.
There’s also a transformation underway in the media industry. The consolidation of various channels and outlets that we’ve seen in recent years is accelerating. Once the COVID-19 crisis is over, the media industry is going to look very different. As we’ll see below, the ability to
Internet Providers Lead the Way
In the post COVID-19 media industry, internet providers will lead the way when it comes to information handling.
Of course, this trend has been underway for years. On the one hand, more and more people are getting their news and information via social media. Simultaneously, paid subscription services like Netflix are replacing traditional forms of home entertainment such as cable television.
But as a result of COVID-19, the prevalence of digital entertainment and news has only intensified. With so many people staying home and practicing social distancing, in-person events and experiences such as sporting events, concerts, movie theaters are being replaced by the ‘new normal’ of YouTube and Facebook live stream events. Once coronavirus abates, it’s likely that some of these trends will continue.
CRM Data Becomes Essential for Success
When it comes to generating revenue, media organizations rely on advertising. But in order to provide paying advertisers with maximum ROI, these same organizations need access to the right
With so many media organizations preparing to merge and consolidate in the coming years, there’s a real potential for larger companies to dominate certain channels and industry sectors. But doing so requires an in-depth understanding of who their customers are — and that means access to the right data via the most advanced CRM software tools. Simply put, large media organizations need to start investing in customer data management if they want to keep their customers happy, attract the highest paying advertisers, and deliver those advertisers the ROI they want.
Learn More About Customer Data Management, CRM Tools, and the Media Industry Transformation
On April 30th AKA Enterprise Solutions’ Media Practice Lead, Adolfo Ramirez, joined other
- Consumer access to content and advertising on-demand
- Social media network proliferation at scale
- Newly digitized media channels
- Effects of industry changes during crises, including COVID-19
Media Tech Trends – How Microsoft Customer Insights Can Turn Challenges Into Opportunities
ABOUT AKA ENTERPRISE SOLUTIONS
Article by: Adolfo Ramirez | 212-502-3900
As AKA’s Media Practice Lead for more than a decade, Adolfo is an experienced consultant and project manager with a history of successful CRM and ERP projects across media and other industries. With 17 years of experience working with the Microsoft business platform, he is responsible for leading his team in designing, building, and implementing solutions that help media companies drive value.
How To Prioritize Education Production For Cloud Software

Cloud software, by its nature, is released through continuous deployment, a regular release cycle that keeps customers happy but sets a difficult pace for the production of enabling materials. Learning departments must develop a rapid decision-making process to keep up with software changes, accommodate to market trends, and adapt to organizational changes.
With a agile content development (ACD) framework, companies can prioritize the content backlog to make transparent quality decisions on education content production in a large enterprise.
The challenge
Running an education team in a large enterprise in the IT industry means your educational materials – videos, tutorials, classroom, or virtual training – must form a cohesive portfolio. You must release them in sync with the software, tailored to the right audience and their needs. Your product is running on a continuous release cycle, and you have resource constraints and limited information about your audience. Being part of a big enterprise also means engaging with many stakeholders: product teams, customer- and partner-success organizations, services, etc., who will come to you with their audience’s needs, ideas, and opinions, all to influence your decisions on what assets your department should produce next. You must also adapt effectively to trends in e-learning and your industry as well as changes in your organization.
So, with so many moving parts, how do you decide which educational asset to produce now? By introducing the content backlog and the prioritization process around it.
To understand it, you need to know a bit about the ACD first.
Agile content development
If your software teams follow an agile development methodology, so should the adjacent departments, like learning. That’s what we did when we created the ACD framework. We borrowed concepts from the agile project management framework (see DSDM) and the scrum agile methodology and adapted them to fit the development of educational material in a large enterprise. Sandra Policht’s post explains more about the ACD.
In agile software development, the product backlog is essentially a prioritized list of product features. This list is dynamic, and each entry (feature) has an estimated effort and measurable value to the customer.
In ACD, the content backlog is a prioritized list of all requests for content. It’s a living document, transparent to all internal stakeholders. Each content request is scoped to determine the estimated effort, and like its software development counterpart, it has measurable value to the customer.
Maintaining the requests on the content backlog is the responsibility of a product owner (PO). In the ACD world, this is a person with an understanding of customers’ needs and what’s essential for them. The PO owns the corresponding education portfolio and has a high-level understanding of product capabilities. Their key responsibility is to continuously and proactively seek feedback from various sources and turn them into requests on the content backlog. The sources usually are customers, product management, trainers, customer/partner success organizations and consultants, feedback from the company’s learning platforms, surveys, etc.
In a software enterprise with a vast software portfolio, a team of POs (with each PO having a distinct area of responsibility) is accompanied by a portfolio manager (PM) who owns the execution of the content backlog prioritization process; and by a project coordinator (PC) who owns production estimates and governs the team of scrum masters (SM) to ensure the expected workload doesn’t the exceed team’s capacity.
To understand the scope of all involved roles and their responsibilities in ACD, refer to Angelina Padarnitsas’ post. Keep in mind these roles diverge from their DSDM and scrum prototypes, and we invented a few new roles.
Prioritizing the content backlog
The content backlog prioritization process is a methodical approach to cope with the competing requests and many different factors/criteria to consider. The process consists of the following four steps, which each PO executes to arrive at the optimal decision for the next production cycle.
Step 1: Measuring against key criteria
For each request on the backlog, the PO goes through the following list of criteria (this is not an exhaustive list but a solid start) and gives it a score (e.g., 0-10). The higher the total score on a request, the more important it is to address it in the next production cycle.
- Business and product strategy: These are the most important criteria to consider. The PO and the education material must follow it. What are the company’s focus areas? Is there a key customer segment, region, or audience? What’s coming in the next product release? What is the company’s flagship product? Is there a part of the product that should be emphasized? For example, the education department may have to support building a software-developer community and therefore would focus production on content for a technical audience and their preferred asset types. POs should prioritize accordingly and give high scores to the content requests that are in line with company strategies, and give low (i.e., 0) scores to all other requests.
- Audience size: While addressing all relevant audience types is important, POs must prioritize proportionally to audience size and importance. For example, POs in a company selling a software framework may prioritize coding tutorials for partners’ developers over end-user guides for business users. Requests addressing the major audience get a high score and those for niche audiences get low scores.
- Portfolio gap: Is each learning path fully covered with content? If an asset is missing in a learning path, especially at the beginning, and for the key audience, POs must prioritize accordingly (i.e., give a high score).
- Release stretch: If an asset (e.g., a video) is relevant for the audience but becomes outdated and far behind the current software version, the PO should give a high score to the corresponding request, low in other cases.
- Feedback: Consider external and internal feedback about content quality and topic accuracy: if it is negative and the topic is in demand, the PO should give the request a very high score.
- Timing: Are there upcoming events, hack-a-thons, marketing campaigns, or other promotional opportunities? The PO will give higher scores to those highly exposed topics and assets.
- Product road map: By staying close to product teams, the PO can identify which elements from the product roadmap may change (be postponed or dropped) and prioritize content requests accordingly: stable topics get a higher score; volatile topics a lower score.
- Product adoption and revenue: Is a product or module in high demand by customers? Content for a frequently used or sold product takes priority over others (i.e., gets a higher score).
- Content adoption and revenue: A very popular free asset (tutorial, video) or a frequently scheduled or high-revenue paid asset (training, e-learning) takes priority (higher score) over less-consumed assets.
Step 2: Defining the scope
At this stage, each PO has a prioritized list with high-score requests on top. What remains is to estimate the production effort and analyze the scope of the top requests.
- Adding estimates: Maintaining the data for past projects is the best effort predictor of future projects – see the roles of the project coordinator and scrum master. The PO consults with the content architect (CA) who has detailed technical product knowledge to ensure the estimates’ accuracy.
- Analyzing the scope: While detailed scope definition of each request is part of the content production (which happens after Step 4), at this stage the PO determines the “must-have” and the “won’t have” from the customers’ point of view (see the MoSCoW method). This approach enables the PO to consider alternative types of assets for the required work. The PO finds smarter alternatives to fulfill (at least partially) more resource-demanding requests, e.g., a video series instead of an extra day of training, or covering a “should have” topic with a trainer demo instead of an exercise for students (a lower system cost). In the end, each request’s scope is reduced to the minimal viable product, but not less. Because POs own the corresponding education portfolio, they keep it clean of duplicates and outdated material. For example, they have the discretion to address a request for new developer training by changing the content of existing assets in the developer learning path. They find smarter alternatives to fulfill the more resource-demanding requests.
Step 3: Deciding
At this stage, POs have all the necessary data at hand to make a quality decision on what to produce next. Thanks to the criteria scoring, they know the importance of the requests and the necessary scope of each (“must” vs. “won’t”). Thanks to the PCs, they know team capacity and how many of the high-score requests their team can address. Thanks to the CAs, they understand the technical complexity, such as introducing demos or exercises (if there are any). POs start to see alternatives and focus on what’s essential. They can, with confidence, decide to reduce an asset’s scope without compromising the quality and still effectively increase learner engagement with the content. In the end, the PO has the content production road map ready.
Step 4: Communicating
The PM and the PO communicate with stakeholders, presenting the portfolio production roadmap for the next production cycle, the decisions behind it, and the team’s capacity to produce the content. Presenting all gathered requests, considered criteria, and explaining the decision-making process prevents disappointment from the more vocal stakeholders. Opportunities for synergy also emerge here, as other teams decide to reuse assets and volunteer to co-produce assets together. After this step, the team starts the next content production cycle; but that’s material for another article.
Summary
ACD has served us well for the past several years, and it’s evolved along with our team to meet our growing set of products, audiences, channels, and organizational complexity. What once was done by a single person now is split into several roles.
Whatever the size of your organization, you will need a repeatable method to make quality decisions on content production. The next time you are under pressure from time and stakeholders, apply this prioritization process or even consider fully implementing the ACD.
Dive deeper into The Digital Workforce Experience: The Shift From HR Tools To Employee Tools.
This article originally appeared on SAP Community.
Explaining Big Data to Your Boss: What to Prioritize
As an engineer, you know what big data means. And your boss might think that he or she knows what big data means. But how do you get your boss to understand what big data really means?
That’s a burning question in an age when big data is one of the most frequently peddled buzzwords of the IT world. Lots of people — including bosses — like to talk about big data.
But being able to talk about big data does not necessarily imply true understanding of best practices for working with big data or how big data drives values for the business.
If you are part of the team of people at your organization who actually work with data, you’re in the best position to help people like your boss to learn to do more than just talk about big data. Here are five strategies for truly communicating the value of big data to your boss.
Size Doesn’t Matter Most
Your boss may believe that big data is defined primarily by its size.
By extension, he or she might think that your organization doesn’t have enough data to qualify as big data, or fail to understand why working big data requires a fundamentally new approach.
This is why it’s important to emphasize that the most important factor to think about when defining big data is how the data is used, not how many gigabytes, terabytes or petabytes the data is.
Everyone Can Be a Data Scientist
Your boss may think that only people who specialize in data analysis are qualified to work with your organization’s data. This mode of thinking encourages a narrow approach to leveraging data.
Remind your boss that you don’t need a Ph.D. to work with data — and in fact, everyone can be a citizen data scientist.
This doesn’t mean that your company shouldn’t employ any data specialists, of course. But it is a reminder to your boss to think broadly about the ways in which employees of all stripes can engage with data in order to help create value for the business.
Data Integration is Key
People who don’t work with data day in and day out can find it easy to assume that data is always neatly stored in the format you need it to be in, that it’s easy to move data from one environment to another, and that ingesting data into analytics tools is as simple as dragging and dropping some files.
In reality, of course, none of this is true except in a perfect world. Integrating data between disparate platforms is one of the most challenging and time-consuming tasks that data scientists face.
Make sure your boss understands this so that you have the support you need to get the right data integration tools.
Real-Time Analytics
It’s also easy for people who don’t specialize in data analytics to fail to appreciate just how hard it is to achieve real-time analytics results — or to overlook the importance of real-time data in the first place.
You want your boss to understand that data insights that are not delivered in real time are much less actionable than those that are obtained from live data. Take the time to explain the difference between batch jobs and real-time analytics, and outline the tools and resources that are required to achieve real-time results.
Again, you want to ensure that your boss recognizes the value of those tools and will provide them to you when you need them.
Data Sources
Your boss should understand what data sources look like. These include both obvious data sources, like server logs, and less obvious ones — such as those that are associated with “dark data” and legacy data.
If your boss appreciates the diverse sources of data, he or she will be better able to ensure that you have the tools required to work with valuable data, no matter where it originates.
Download our eBook, 2018 Big Data Trends: Liberate, Integrate & Trust, for 5 Big Data trends to watch for in the coming year.