Business Goals as Friend or Foe: How to Keep Focused when Building an Analytics Program

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In this special guest feature, Lynda Partner, EVP, Data & Analytics, Pythian, discusses the top business drivers for analytics programs and how, depending on each one, a company might shape an analytics program differently. Lynda is a self-professed data addict who understands how transformational data can be for organizations. In her role as EVP of Data and Analytics, she focuses on Pythian’s services that help customers harness the power of data and analytics and holistically manage their data estate. Lynda’s love affair with data started 20 years ago when she founded a highly successful SaaS company that took advantage of data to increase product usage and generate revenue. She continues to make daily data-informed decisions to achieve faster and better results with measurable outcomes, working with companies around the world and across industries to turn data into insights, predictions and products. Lynda holds a Bachelor of Commerce with honors from the University of Ottawa.

Sometimes when building relationships, you might find yourself wondering, “is now the right time to invite them over? Meet my friends? Meet my parents?” It can be hard to know which path to take and at what speed to travel.

Those of us who’ve run data and analytics programs might have wondered similar questions. Are we at the point to do X yet? When will we hit our next milestone? When will needed insights be easily available?

Analytics exist to support the business. It’s a seemingly obvious statement, but it’s one worth repeating – and repeating. 

All too often programs fail because they lose sight of where they’re going. Time, effort and care goes into cleaning and organizing the data. Dashboards and reports are built. Money is spent. And yet no matter how pivotal, how transformational the data, if we’re headed in the wrong direction, we’re headed in the wrong direction. 

Then before we know it, business goals have turned into data’s foe.

It can happen for a few different reasons. Without adequate oversight, a pilot program turns into a full-scale venture. Organic growth happens quickly, outpacing governance. Ad hoc programs across the company duplicate efforts, create gaps or, the worst-case scenario, result in more than one source of truth.

The first step, no matter the challenge, is always to take the time to align the program to core business needs. Make sure they get friendly with each other. That they understand the other’s value and stay connected throughout their lives. 

Together, data and core business needs create the overarching strategy that grounds their relationship.

It’s this partnership that can rally cross-functional support of real-world priorities, clarifying how the business will use its data, as well as the insights and information data produces.

Top business goals for analytics programs

A data and analytics program is judged based on how well it contributes to business outcomes.

To illustrate, here are five top business goals:

  1. Grow revenues
  2. Increase operational efficiency
  3. Strengthen customer experience
  4. Drive innovation
  5. Improve compliance

When a program focuses on at least one – in combination with open communication – it generates transparency, focus and engagement between both business and IT stakeholders. It helps prioritize the most important requirements for success and gives an effective way to measure impact.

Yet as you can imagine, each goal shapes an analytics program differently.

Grow revenues

Let’s say a retailer wants to grow revenues among its existing customers. An analytics system designed around increasing conversion would be a worthwhile program for them to explore building. 

It could predict a customer’s propensity to buy and deliver data about them to a marketing automation platform. That makes hyper-targeted promotions, incentives and other marketing efforts possible, contributing to growing and retaining their customer base.

Increase operational efficiency

In manufacturing, efficiency reigns supreme. Operational expenses, including unscheduled maintenance, can cause delays and rack up costs that can negatively affect the project’s timeline as well as bottom line. 

If a manufacturer’s goal is to increase operational efficiency, they’d benefit from analytics that use sensors on production equipment or trucks. This type of data, in combination with other data, can predict when maintenance is needed well in advance, helping to prevent breakdowns and other issues.

Strengthen customer experience

Customer experience is a big one these days, with many companies across industries trying to find their footing and their niche in how they interact with customers. 

For online gaming, in which the goal is to keep users engaged for as long as possible, the right analytics system makes all the difference. It could support real-time, in-game adjustments that match the individual’s skill and style to level of play – a degree of sensitivity that can help maximize in-app purchases, ad views and more.

Drive innovation

The secret to innovation is empowerment – empowering people and business units to follow their curiosity and experience to uncover the next iteration, generation or modernization.

Analytics can be truly pivotal in such efforts. Self-service analytics, an approach that makes data easily accessible to many in the company, matches the level of independence discovery requires. To make it possible, the data platform needs to be able to provide access to different types of data and serve a variety of user types.

Improve compliance

For companies in which privacy regulations are a requirement and improving compliance is a top priority, analytics programs could focus on indefinite storage, logging changes to data and providing conclusive evidence of its origin and use. They could track the source, use and enhancement of all personally identifiable information in its systems.

Befriending data for business transformation

Data and business goals are a match made in heaven – each giving the other what it needs to be meaningful, productive and successful – but that doesn’t mean the path starts clear and paved. It’s up to those of us across the business and the development team to focus the program. Together with our data, we can transform business outcomes.

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