How to Achieve the CDO Mindset

The CDO (Chief Data Officer) Mindset

I’ll be reviewing how technical implementation, development and solution design teams can utilize the CDO mindset to bring a more ‘strategic vision' for success to high complexity projects. While attaining the skill set of a CDO is daunting, having the CDO Mindset can be achieved with amazing impacts to teams, projects and output.?I've tried to keep this article sized for an easy read with simple use cases so the reader can walk away with immediate actions to take. Input appreciated. Enjoy.

Skillset

Lets start with what a CDO or Chief Data Officer is and what is the required skill set? CDOs run the gamut for data in large company organizations and are responsible for the development and management of all data assets , associated teams, supportive technologies, security, governance and workflows. That’s a lot of responsibility and thats only a small list of items that the CDO is accountable for. CDOs are required for larger companies that carry a complexity of technical and business systems to meet their customers and partners needs.?

By high complexity projects I am referring to organizations with 5+ systems with many integrations, disparate account and/or asset data (*asset hierarchy), duplication and standard formatting, warranty, contract and SLA visibility for field service and many other items too long to mention here. The scale is large where the impact can be felt throughout different divisions and across multiple roles.?

So how does this transfer to the CDO mindset?

Mindset

To achieve the CDO Mindset you need to have a ‘strategic vision’. The only way to approach the ‘strategic vision’ challenge is with a structured approach to data that provides a clear roadmap (or plan) of milestones that lead to proactive and innovative outputs like predictive analytics and streamlined access to the right data, to the right person, at the right time be it a sales or service call or work order. A roadmap should also have a clear definition of ‘done’ in the milestone journey with the ability to measure whether you are on the track to success and whether you have achieved it or not. I ask all my clients “how do you know when you are successful?” Start with this question and be prepared to guide your clients. This is now part of your job.

A good example is to have an ‘integration strategy’ with a clear understanding (via a CoE perhaps mentioned below) of what you are trying to do with this data from a business (people), process or technical perspective. That means having a visual system model showing where the systems are, how they are linked and what data type is in each system. In more detail, you will need to rate the value of the data, provide details on whether it is actionable, dependent and or supportive. You will also have to rate its maturity and state - by state I am referring to the work needed to transform to the Target data standard or data state.

Action: To provide this clarity, you will set up correlating sheets to the system model that provides this information (*one per system to start). It should be simple in design (use PPT if you have to, just get it on the page), easy to understand by all divisions, business or tech with clear labels correctly stating the items and what they do. Take a screen shot of the Model(s), put it on the first pages of the Excel sheet and reference this as you create each system per sheet. It's quick and it gives you clarity as a functional working document. That's what you want. This is your template for success. Don’t skip it. You can always make it pretty later for the SDD (Solutions Design Doc).

An important part of this mindset is to always think of the organizational ‘data as an asset’. Like the service and product offerings the company offers, data drives the customer and employee loyalty, revenue, insight for competitive relevance and much more. Your predictive modeling which feeds your AI model is based on the data you have in your system. You are offering data to your clients as a service whether you know it or not. Think Amazon recommendations. Do you know who and when to introduce a product or service to a client to help them achieve a challenge or requirement? It drives the trust your clients and customers have in the company which brings us to the next item.

Do you trust your data?

From a CDO perspective,

• What needs to be done to have a data trusted platform?
• How do I ensure the data can be trusted now and in the future?
• How do you think this can be solved? (the plan working backwards to actions and milestones)

The first rules are that data should be brought up 'early and often'. Templates should be at the ready (*see 'Action' above for example). Sets of the client data should be reviewed before the project starts with the team. My teams and customers always underestimate the data management side of the project and it usually extends, to everyones surprise, all the way through the project. It is ongoing in each sprint. It is never easy, always more complex on secondary passes and many times you will find additional data sets and systems that you will need to deal with. Btw, who was supposed to clean up the thousands of records? We thought you were doing it, we don't know how. Assumptions = project death. Don’t be surprised - be READY.?

As the volume of a company’s data grows, so does the complexity. There is historical data, 3rd party data, actionable data that all needs to be mapped to the system of record for an actionable 360 view of the customer. There is also the expectations of your customers as their security and personalization expectations increase. So how can a technical team manage complex projects to achieve real transformational change. First, lets figure out what real transformational change is. Lets go back to the question, “do you trust your data to make key decisions for your company, its customers, employees and stakeholders?” Now, put a number on it. From 1-100 how confident are you in making key decisions based on your data and can you identify what and where the gaps are? The gaps are where opportunities for growth lie so write these as real requirements (real addresses the Who, What, Why/Value) and add to the backlog for safe keeping.

Author Robert Greene speaks to the power of planning and building backwards to become a technical and business visionary. From the movies of Hitchcock to the battles of Napoleon you must be able to move above the noise and complexity to see the larger strategy. That is what we can achieve with the next three steps which is the point of this article. Begin here and expand to build more sustainable systems, streamlined data output to provide a real 360 view of your company assets (Products, Services, Data) and in the process drive confidence in the calm and clarity that is needed when things become demanding which they will.

Lets review 3 steps to start the journey.?

Step 1: Single Source of Truth for source function.

The first step is to address the data in all the areas of your organization. Data must be consolidated so that it is actionable (consumable) on a centralized platform. This is the primary action of achieving your strategic vision. Without a clear data management plan you will be on your heals in a reactive state, this is more than being proactive. This is about having control and seeing years ahead so that you can be a guide and trusted leader to all teams. As Martha Stewart says, you can’t have a little bit of control - you either have control or you don’t. Well, here is your first step to having control.

• To get started, work on the ‘strategic integration’ plan mentioned to identify where all the active data is and if its usable. This will provide you the clarity to confidently move to the next step.
• Other actions are as follows: Controlling multiple versions of data records and duplication of data as data may not always come from just one department. A simple use case is when sales makes a call they may update the contact number or email, but when service teams follow up with the customer, their information is not updated. This bleeds to the field service teams that need the most updated contact information for job kick offs, sign-offs and notifications and follow ups. Apply this to a complete system lifecycle and you are going to have serious issues.
• Impacts can be seen in items like emails, location addresses, asset locations, moving client contacts, to name but a few for only contacts. If its a 3rd party system this adds more complexity as the data format may be driving a process or actions around records and assets. List these as requirements and get it in the agile system right then so you and your teams can build out those user stories in the backlog. This way you will have created your components or Epics and it will be easy to filter and organize these stories later (parent > child as well).

Step 2: Making data available for ‘active and valued’ consumption.?

An example is a recent client that had data in different source systems but not at the valued Case record where it was needed to take action. Having data available at the system of record to be active (consumable) meant going through multiple data ETL processes per system. (*I won't be discussing component models of Mulesoft or ELT vs ETL in this article due the goal of having immediate actions you can take today - additional articles coming on these items later).

• In some cases the source systems needed extensive work to get the data to a state that was valued or acceptable (maturity rating) to create an active and worthy Case. The Source teams wanted the Target to take the burden but that would mean in some cases triaging 100s of Cases per day where only 10% would be relevant. Not a great way to utilize your man power nor is this ever sustainable no matter how many automations you put behind the process. Address the Source.
• Making data available at the point of decision making or to give context (support) for decision making is the goal here, not how its going to be delivered. It goes back to attention to your Source systems to begin standardizing the data to support the Target system. As mentioned in my example above, Source systems will be at different 'maturity models'. Some data will need to be kept at the Source systems and therefore, each must have its own roadmap to reach the ‘maturity metrics’ required and defined by the Target before it can be passed over in a consumable state.
• Use a standard format for data transformation. Ask your clients "What should data look like?" "What should it tell us?"? Use templates for case studies to identify the requirement or problem you are trying to solve. Its always good to track what your teams did to solve the problem? From this you set standards for historical data which can be used in predictive modeling scenarios.

Step 3: Infrastructure Modernization for systems, processes and structures.

Infrastructure Modernization is the next step to meet the emerging needs by modernizing system structures with tools and platforms. The process should be well planned and continuous.?Excite your employees and customers when tell them about the new system(s) and how it benefits them and keep them updated as the projects progress.?

• Center of Excellence (CoE): To manage the moving pieces its best to create a dedicated CoE (Center of Excellence) to meet at designated times to address the companies ongoing digital transformation strategy and timelines(LINK). The best teams use them to keep the company from working in siloes.
• Look for technology that works nicely with your current divisions and systems be it your ERP, CRM and Mobile. Bring your customers closer with customer and partner centric personalized portals, messaging and notifications on their accounts and interactions on the challenges and successes of your products and services. Now if an issue or opportunity comes in it will be immediately identified and smart automation and triage processes can be applied.

Exploring the CDO mindset takes time and diligence in setting up a process that works for you. This being said, the above points have been used on some of the largest most complex projects I’ve been on. Don’t invent the wheel. You don’t need to and you don’t have time to experiment on your customers or clients. Not cool. So get control. Become a data guru with a strategic vision that you can confidently stand behind. People need this and there is no excuse to wing it now that you have read this article.?

Put on a good show for the Gods. Now go get em.?

I’ll be covering these 3 items in more detail in future articles. Be sure to follow and enjoy the content.