Defining your Data Strategy

Defining Your Data Strategy

Why is Data Strategy important?

Your Data Strategy aligns your efforts with your Data Vision and Data Mission Statements.  It brings forward all the necessary elements (People, Process, Technology and Data) to derive value from your data in a straightforward manner that you can execute.  Your Data Strategy is also a critical communication tool that ensures the organization will support the initiatives and provide the necessary resources.  Most importantly, it brings your organization to the next level of detail where people can see what will physically be created or changed.  Ultimately, they should be able to see how the Data Strategy will help the organization.

 

How to get started:

Most data strategies are based on a simple concept of how you get the “right” data into the “right” people’s hands so they can make an “informed” decision.  Data strategies are becoming even more important with the growth of Data Scientists and AI.  Every organization is different, which is why the Data Vision and Data Mission are critical.  Combining this concept with those statements creates your strategy. 

An important decision to consider: Is this strategy going to be a digital transformation where you radically change how your organization operates or is it going to focus on fully integrating data into how you operate today?  There can be a benefit to becoming a data-driven organization and truly understanding your data prior to a full digital transformation.

Some strategic questions to start with:

• What data enables your organization’s vision (and mission statement) and who uses it?
  • This is an excellent exercise to take both a top-down (strategic) and a bottom-up (operational) approach to see how well they align. 
• How is data used today, and are there areas for improvement?
  • Most organizations have known issues. However, in many organizations those issues change as people create workarounds or even create data to meet their needs.
• Does your organization have strategic initiatives in the planning stage or underway?
  • Can you identify the data that will enable its success?
  • Can you identify who will use the data along with how and why they will use it?

 

During these discussions, it is essential to incorporate each of the data strategy elements (People, Process, Technology and Data) to get a broad understanding of how the future state will function.  Each of the elements will allow you to segment and group your needs into definable efforts.  From this effort, you will create a series of high-level data needs that can be structured into objectives and capabilities.  It is crucial to stay at the objectives (or needs) and capability discussion level at this point in the process.  Solving for these objectives will come from the assessment and road mapping activities that are coming up.  However, it is also important to start to put a value and priority or ranking on the objectives.

 

Start by framing up the discussions based on the core elements.  Each of these data needs or capabilities will incorporate the following four core elements to varying degrees.

People – Who uses your data and why? What skills and experience do you need to execute the strategy and reach the vision?

Process – How is data used in your processes? What procedures are needed to derive value from your data?

Technology – What are the capabilities you need to reach the vision?

Data – What types of internal and external data do you need? What level of data quality and how much history do you need?  What level of integration and security do you need?

People

We start with people since one of our clear objectives is to ensure we get the “right” data into the “right” people’s hands.  It is also why we end with data so that we come full circle and look at our data to see if it aligns with our people’s needs. 

People like processes, technology and data when they are helpful, easy to understand and to use.  Using the lens of how people perceive and interact with each of the other components gives a strong foundation for making the right short and long-term strategic decisions.

There are several benefits to using people for building out your data strategy elements. 

• First, most organizations’ vision and mission statements relate to people. The Data Vision and Data Mission statements reflect these goals.  This is important when you are evaluating why each of the components is valuable to the organization.  The more tightly correlated your strategy and each component is to the organization’s vision and strategic initiatives, the easier it is to put numbers to that value. 
• Second, processes inherently involve people. It is easier to understand how data is created or consumed in a process when you look at it from the people’s perspective. 
• Third, technology is an enabler for people. Designed and implemented correctly, technology can dramatically improve your organization’s efficiency and effectiveness. 
• Fourth, people are the creators and consumers of data. They define data quality and data security for their needs. 
• Finally, using people as the framework creates a foundation for your change management effort, which will lead to faster adoption and shorter time to value.

 

The first step in utilizing the people element is segmenting all of your stakeholders.  Segment at a strategic or high level to start.  Internally you may segment by function such as Sales, Operations, Finance, etc.  Externally you have vendors, customers and the rest of your ecosystem.  For some organizations, these may need to be broken down further.  In our previous article, we used Amazon as an example.  Amazon has different customer segments, meaning an Amazon Prime customer will have different data needs from a business using AWS.  As you get into the Assessment and Road Mapping steps, these groups may be broken down even further.  At this point in the Data Strategy, you are looking for the commonality of needs that can be grouped together by the other elements of Process, Technology and Data. 

 

Process

The second step in framing up the discussion based on the core elements is looking at your organization’s high-level processes and understanding what types of data are needed to support the process.  Some examples for different companies’ sales processes:

• Company “A” sells services to businesses. They have a complex sales cycle and large sales funnel.  They have many prospects for new customers and are always trying to get repeat business from existing customers.  Their references from existing and past customers are critical to closing new customers, and their success with existing customers is crucial for future work.
• Company “B” produces consumer products that they primarily sell through a retail distribution model. They have “customers” who are the retailers and “consumers” who are the end purchasers of the products.  Their sales team focuses on gaining distribution through their customers, while their marketing team targets driving demand from the end consumer.

While each of these examples shows high-level sales processes, the data needed to support each process is very different.  For company “A,” having data to show success at delivering services in a specific industry as well as understanding the vital prospective customers and influencers will be crucial.  Whereas for company “B,” having third-party data that shows their product’s growth or dominance in the market will help them leverage better deals with their “customers.” Company “B” can also use data to see the effectiveness of its advertising, PR and promotions across all their media channels to ensure they invest wisely in driving “consumer” demand.

One benefit of looking at your processes through a people and data lens is that the processes themselves can be simplified to get “better” data into the people’s hands faster.  You may also discover that additional data may need to be created or acquired to improve the process.

 

Technology

Now that you have a view of who needs what data for your organization’s high-level processes, we will focus on how your people use the data.  What capabilities do they need to succeed? Again, we use the people lens and segment based on stakeholders.  Some stakeholders are very data and technology savvy, such as your analysts and data scientists.  However, some may just need a quick view of specific data to keep their process moving forward. 

• What data do they need?
• How fast do they need the data?
• Do they need to manipulate it after they get it? Could the system provide a complete answer without manipulation?
• What happens next? Is new data generated? Is existing data modified? Is data sent to others for their use?

KEY QUESTION – Is self-service an essential capability?  Self-service for data access and manipulation is incredibly powerful.  However, it requires a larger investment in your technology, data and people to be successful. 

Data

We finish with data to ensure we get the “right” data into the “right” people’s hands.  What is the strategic data for your organization?  What are the key subject areas?  Do you need external data?  Who will own the data by subject area?  Are there known critical gaps in your data?  Which is the more significant need – providing access to your data or securing your data? Finding the balance between these needs is critical.  How much transparency do you want to deliver across your stakeholders?  What is the perceived quality of your data? Does it meet your current and future needs?

There is much more detail for all areas that will come out in the assessment phase.  Your output from this Data Strategy effort should provide clear direction, objectives and capabilities that lead to clear assessment goals and roadmap.

 

Some examples for your Data Strategy’s key objectives and capabilities:

What	How	Why	Value / Need
We will enable our customers to see a 360 view of their account	Provide payment history, payments due, order history, current products on order, delivery status and available product inventory	Drives higher customer satisfaction and lowers customer support costs.    Takes friction out of the process and will increase sales	·        $ to $$ ·        Redeploy headcount ·        Increase sales
Our sales, operations and finance people will see fully integrated forecasts	Pull together all forecasts using a common data set.  Integrate the forecasts with known capacity constraints in our supply chain and critical deadlines	Accuracy of our forecasts and flexibility in our supply chain are significant drivers of our profitability.	·        $$$ to $$$$ ·        Complex ·        High Value ·        High Priority
We will provide seamless customer and product data to our salesforce	They can see current status, open issues, history along with customer and product profitability	Blending Customer Relationship Management (CRM) data along with operational, historical, customer and product profitability will build a stronger and more profitable relationship.	·        $ to $$ ·        Low to Medium Value ·        Lower Priority ·        Simplifies what is done manually
We will publish our top 4 Key Performance Indicators for all employees	Provide a portal (accessible through a secured device) where every employee can drill down and see how their efforts are making our organization successful	Transparency and engagement build a more motivated workforce.  Many great ideas and process improvements come from people understanding how their roles impact the organization.	·        Medium Value ·        Medium Priority ·        Is dependent on other initiatives

 

These objectives and capabilities need to be clear so that you can use them to get support to move forward with the strategy from senior leadership and gain trust from the entire organization.

Article four, the Data Strategy Assessment, will take these objectives and capabilities and integrate them into your organization’s processes and overall technology strategy.  The assessment looks at your current state and focuses on what is needed to deliver on these objectives and capabilities.  We also add the Data Strategy Structure and dive deeper into technology, costs, and ROI.