5 Principles for a Modern Data Strategy
Taylor Culver

Taylor Culver

Apr 2020

5 Principles for a Modern Data Strategy

Having worked with a handful of organizations trying to launch or improve upon their data strategies it’s evident that a pattern is emerging. Organizations have made tremendous investments in data but are having less than desired outcomes than originally intended. The reality is that many outcomes were solutions led, that the business has inherited over time, and has not been resourced appropriately to maintain or improve upon the original investment.

Having worked with a handful of organizations trying to launch or improve upon their data strategies it’s evident that a pattern is emerging. Organizations have made tremendous investments in data but are having less than desired outcomes than originally intended. The reality is that many outcomes were solutions led, that the business has inherited over time, and has not been resourced appropriately to maintain or improve upon the original investment. 

 

Furthermore, data teams are being spun up to fix the problem; but absent a clear objective and sponsorship they become an added layer of complexity. Today, now more than ever, it is critical that we revisit our data strategies more than ever to achieve the benefits of machine learning, predictive analytics, and robotic process automation. Business intelligence & reporting is not the stopping point, but rather the beginning.

Purposeful:

  1. Data is not a project, solution or team but rather an ongoing service to the business similar to operations, HR or finance.
  2. Doing nothing with data is an acceptable strategy if there is no business benefit to doing something.

Empowering:

  1. An individual should be held accountable to an organization’s data strategy
    1. This individual is entitled to executive sponsorship and adequate resourcing to do their job to the best service of the organization
      1. If this individual is not resourced appropriately, they are put in a position to fail at which point that individual should consider resigning from the position
      2. If this individual does not resign, they should be reassigned by their manager as data projects can lead to more distraction and negative impact if not properly staffed or managed

 

  1. Having a departmental data strategy is acceptable assuming the organization is willing to carry redundant costs across the organization.
    1. It is common for data to emerge out of a department as different departments carry greater sophistication in their analytical needs than others
    2. When two departments have data teams, a single individual should be put in place above both for oversight.
    3. In the long term, having parallel teams for data will create greater organizational complexity and productivity loss than the efficiency it affords each departmental need

Impactful:

  1. In turn this individual is accountable for demonstrating tangible business impact from managing data.
    1. Offsetting risk, new insights, being innovative, implementing a solution are not avenues for positive & tangible business impact
    2. The only way to demonstrate tangible business impact is through data initiatives that drive financial benefit to the organization.
    3. By eliminating data driven inefficiencies, productivity can be improved
    4. If productivity is improved and no action is taken and there is no economic benefit to the initiative
      1. If the cost of the initiative is greater than the productivity gains identified the project should be stopped until the benefits are better understood
        1. Time spent discussing what data means, manipulating data manually to produce content or improve data quality are all sources of lost productivity.
        2. By identifying redundant software spend or removing poorly adopted technology solutions relative to their costs, data teams can drive cost out of organizations
      2. Licensing data is a means to data monetization
        1. Licensing is difficult for many organizations to achieve and is a less probable outcome for immature data team

Engaging:

  1. Critical to achieving this business impact is driving engagement with the data community.
    1. The data community consists of any employee that uses data in their day to day whether it be accessing data from a tool, spreadsheet, or receiving information from another person to make organizational decisions.
    2. Data consumers are going to be engaged to various degrees from detractor to enthusiast
    3. Rather than try to change the personas you are working with, understand what they want and need to achieve their data related needs
  1. The data lead must source common business needs across data consumers to clearly defined use cases
    1. A use case must have a sponsor, a business impact, and a clear goal
    2. A use case is more compelling with a greater business impact, number of users with the lowest risk and complexity
  1. The data lead must work with the business to document data requirements at the metric level before solutioning for the problem
    1. Key business terms, definitions and owners must be established and mapped to a use case
  1. The data lead must map business terms to what is in physical systems, as opposed to mapping physical terms to business terms
    1. Giving the business all the tables and columns in the database and asking them to define them is a waste of time and extremely frustrating
  1. Identify solutions that solve the problem within the scope of the overall use case
    1. Use cases with common solutions can allocate the cost of those solutions across those use cases
    2. Buying a solution before identifying a use case is a recipe for failure
      1. This is a known fact, but it doesn’t stop people from making the same mistake – be courageous

Transformational:

  1. Effective Data Governance is the operationalization of the principles above
  2. Data Governance meetings become conversations about use cases and timeline for delivery, followed by driving consensus on metrics with overlapping use cases
  3. New business needs can be added into incremental use cases
  4. Omitting any of the above steps will lead to likely lead failure of a data initiative

 

XenoDATA™ is a boutique management consulting firm partnering with you on making your data strategy successful. We strive to understand your core data issues through a business lens, and partner with leading technology providers to achieve these goals both in an implementation and advisory capacity. Companies cannot afford investments in technologies that do not produce results. XenoDATA™ work to empower teams with strategies and technologies that drive financial results.

 

Our services include data strategy advisory, data product development, and analytics implementations

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Organizations We Have Helped

We pride ourselves on driving tangible business value out of data for our clients. Whether it's starting with you on the ground floor, or jumping into the deep end of your initiative we help clients through developing and honing meaningful data strategies with business impact, along with the implementation of forward thinking data products & data analytics solutions.

Innovative Insurance Brokerage

Our client was facing issues with scale and innovation. They had a core business that was growing and a team of key players but sought incremental growth opportunities.

Seeing a need to drive innovation and technology enabled scale within their services business. Our client set out to build a data-driven platform to automate and align all parties involved in their process to a common platform.

Client built and designed data centric platform and began the process of taking to market with their existing customer base.

World's Largest Brewer of Beer

When it came to data strategy, management, and execution, our client was looking for a second set of eyes. Although the client was aware of the problem, they couldn’t close the gap with technology alone. They lacked an actionable playbook and strategy to operationalize their data ambitions.

Build out executive level playbook to address data opportunities and risks, while aligning to organizational data governance committee to drive forward cross-functional data initiatives.

Data silos were broken down leading to operational changes in enhancing business systems and requesting reports. Projects came with significant P&L impact driving incremental inertia into their data strategy plan.

Technology Enabled Services Firm

With disparate data sources for operational, financial, and customer data, all with different structures and content, executives, team leaders and individual contributors were all operating on different systems and completely misaligned.

Our goal was to ensure we developed a customized, unique solution to improve their services, business intelligence, and their value for internal and external customers.

After taking the time to understand the core data problems of the client beneath the technology and developing the customized solutions to meet their complex challenges, they began to notice results. As a result of our partnership, they saw improved information access, streamlined reporting and an increase in the overall quality of the data of the organization.

Largest US-based Beauty Retailer

Our client was working to offset the risks associated with CCPA & GDPR by documenting and storing all organizational knowledge.

Design business oriented data definitions and map to data in physical systems.

Single repository for all data definitions along with accompanying playbook to drive greater engagement.

What Our Customer's Internal Stakeholders Really Care About

Every company has data. Not every company has a Chief Data Officer. Data oftentimes is a part time job for many. We oftentimes see this manifest differently depending on the role we're working with. You are heard, and we want to hear from you!

Executive Leaders

Drive Competitive Advantage With Data

Allow your data to give you the brilliant insights to need to get ahead of the competition. How you handle your daily operations to your marketing efforts – every piece of data gives you the ultimate competitive advantage.


Clear Organizational Data Strategy

As an executive leader, it’s all about the big picture. Your data strategy must be consistent across the organization to ensure every department is aligned, working towards the same goal and accessing unified data.


Capture Real Data Opportunities

All to often do projects get escalated with high costs and purposeless urgency. "Didn't we just do something like this?" Cut through the noise, get to the facts.


Integrate Data into Every Part of Customer Journey

As you put yourself in your customers’ shoes, how is their experience? Are you sending them outdated, stale, and clunky information without personalization or relevance? Can they consume your data in new or interesting ways?


Direct Data Revenue Attribution

Your data can provide deep insights to better understanding your current and unseen future streams of revenue.

Data Leaders

Culivate Single Source of Truth

Aside from it being incredibly inefficient, sifting through multiple datasets trying to uncover which data is accurate, real, and true causes confusion and frustration, with the potential to have serious internal and external consequences.


Drive Business Ownership of Data

The question is simple – who owns your data? If you don't know, it's probably you. This is a problem.


Improve Data Governance


How you organize your data is much more than just a classification system – it’s the ability to provide quick, timely across to make for happier customers, leaders and fellow colleagues.

Have Exceptional Data Quality

Every piece of data you collect starts to tell a story. Perhaps it’s about a customer’s unique preferences, or maybe it’s related to product performance.


Minimize Data Related Redundancy

How many tools, teams and databases contain or process the same information for the same customer?

Department Heads

Have Powerful Business Insights

As you uncover each piece of information and patterns emerge, it starts to tell a story. Every department has the ability to rapidly transform and innovate – and it begins with the intelligence and analysis of your data.


Increased Team Efficiency

Instead of having haphazard departmental analyses throughout your organization, take ownership for the data you truly need and want.


Data Availability and Transparency

Each company has their own objectives and key results for success – and they often require multiple datasets to get there. This will help to create a culture where data-informed decision making is the norm.


Better User Experience

Depending on the specific function of your department, it’s all about the user experience (both internal and external). To keep your employees and retain your clients, you must think about offering the best user experience possible – starting with your data.


Remove Perceived Roadblocks

As a department leader,it can feel incredibly burdensome to get even the simplest of tasks done. From sending out a marketing email to generating a customer report, sometimes what seems like it should take a few minutes turns into a few months.

Dozens of customers have trusted us to identify and capture millions of dollars of waste due to poorly managed data.

Anheuser Busch InBev Ulta Beauty Williams Lea M&A Insurance Solutions