The Case for Why Marketing Should Have Its Own Engineers

Today, he runs the marketing team like an independent agency within the organization complete with its own engineers — a strategy he highly recommends for small teams that need to get a lot done fast.

An interesting article to set up an in-house agency to support all of marketing.  As a database marketer, I truly believe the team needs its own database and its own engineers to maintain this database.  It has to be separate from the IT processes that slow down progress.

Why?

Why shouldn't marketing data be included in the rest of the organizations data?

The simple answer is time.  Most data put into data warehouses are used for analytics.  Sounds just as important right?  Analytics is the driver of making money in the organization correct? 

Sort of.  This data can also include financial data that has different processes based on financial rules, especially for public companies.  Some data might include credit card information, which need to be PII compliant.  This data needs strict data governance and encryption of sensitive data.  All of this takes time.

Time is the enemy of marketing.  The amount of time it takes to get data into a marketing database relates to an amount of revenue that is being lost.  Most data requested into a marketing database is used right away in segmentation for campaigns.  These campaign changes either drive revenue or save on expense.  Having engineers able to get data into the marketing database in an expedited process gives an organization a competitive advantage. The quicker new data equals the more efficient database marketers.  All this leads to more money to the bottomline.  

Interactive Data Visualizations - It's Still About the Data

With so many data visualization tools out in the marketplace, it is a wonder why most organizations are still struggling to get these easy to build dashboards adopted throughout the organization.

It usually comes down to the data.  The data still has to be accurate and up to date and reliable.  So many organizations still struggle with this.  I believe it comes down to structure within the organization.  How does IT still control the data in many organizations?  IT tends to create processes and documentation that takes data forever to get into the hands of the users.  

It all depends on the size of the organization.  When organizations are very large, this type of process and documentation is needed.  Most organizations are not this size.  The data is used by a handful of people within the organization and a more agile approach to data needs to be taken to always have the best data at the soonest possible time.  Long lead times and processes that make moving things forward difficult lead groups within the organization to get their own data in many different ways and this leads to many different versions of the truth and lack of trust in the interactive dashboards.

Organizations need to move the data ownership into the hands of the data users to ensure one version of the truth.

The Chief Data Officer: An executive whose time has come

I often ask people whether they know what Netflix, Harrah’s, Amazon and Wal-Mart have in common? The answer is pretty simple. They use data analytics to leave their competitors in the dust. Many other businesses are trying to do the same, spending millions of dollars on data software.

It takes more than a steep investment, however, to squeeze business value out of data. Companies have to establish an entire system to use data to drive competitive advantage.

Data as a competitive advantage needs a department that is responsible for the analytics and getting all the needed data.  The data owners and the data users should reside in the same division to ensure the right data is always available and up to date.  Also, the decisions on resources should be within that department, not within IT.

When IT is in charge of the data, they tend to not understand the business as well as needed to facilitate data.  The operations does not understand databases and technology, however the analysts understand the business and the technology, so they should own the data and the facilitation of the data.  

Bridge the Gap Between Marketing and IT

...IT organization has been transitioning from the traditional development approach of (1) define functional requirements, then (2) design, then (3) build (the "waterfall" approach) to making quick, small changes to systems ("Agile Scrum").

The waterfall approach kills companies that are not in the software business.  Since internal products are not sold, nor measured by sales, its easier for IT departments to hide behind process.  Process and requirements kill companies.  Companies in this current age need to be faster to market.  

Agile and Scrum have allowed ING to respond quickly to signals from customers. But moving to continuous delivery is a struggle. Some business people who are used to the traditional waterfall method can fall into an unfortunate cycle: taking months to develop requirements, then waiting for IT to respond, then telling IT that's not what they wanted. Now instead at ING they say, "Here's your team. You need to be in every daily or weekly Scrum cycle or sprint to decide if the work is meeting your needs." It demands more time from the business people, but they are engaged and own it.

The Agile method is so much more effective to engage the business.  The business moves at the speed of sound compared to IT and if the IT department gets buried into process, the business loses faith in IT and finds another way.  This doesn't make sense for the business, but it happens to get things done. 

While Scrum has been employed primarily in software development, ING shows that it has broader management applications. They have used Agile Scrum as a key tool for collaboration across functions in processes such as developing new products and in marketing campaigns. And the frequent (daily or weekly) meetings accelerate decision-making.

This is very interesting and I have never thought about all decision making changing to an Agile Scrum.  In my business, I deploy an "unofficial" Agile Scrum, just have never thought about it from that point of view.  I believe it works so much better, to be engaged daily in your business and with your team.   

 

Manage Data with Organizational Structure

Article on who should manage data...​

most people management is actually done in the course of day-in, day-out work, by managers and employees. HR may very well define the semiannual performance review process, provide the needed forms, and make sure it is carried out. But performance assessment is completed by employees and managers.

This last point strikes at the heart of the federated model. Corporate HR sets policy; department HR may modify it in accordance with specific needs; and departments, managers, and employees carry out these policies. Most have a certain degree of latitude in how they do so.

 I am a big proponent of moving data management out of IT.  The HR model is exactly the model that works.  The business is closer to the data and very few IT department can handle the pace of the business when it comes to data management.  IT designs the network, builds the hardware and manages updates, while the business manages the ETL, data model and governance of the data.  

Will Data Science Become the New Bottleneck? - Forbes

many have posited that recalcitrant IT departments, hidebound by a history of rigid organization, have been a bottleneck to the adoption of new technologies and, by extension, the ability to distill business value from data.

We’ve also examined the potential and difficulties of analyzing big data, arguing that a new class of analyst, the data scientist, is on the rise in many organizations.

That may be part of the problem, rather than the solution.

I think this will be a major problem as big data moves into the mainstream.  So many organizations struggle with IT getting data that is readily available in the organization, wait until 20 groups are pinging 2 data scientists, who by nature are slow and go down unnecessary rabbit holes to find the truth.   

In reality, most businesses don't need all this data.  They need to perfect using their current data to drive actionable results.  Until they do that, there is no need to bring big data into the organization.  ​