MOPs and Data Science: How to Get the Green Light on Collaboration

TLDR: The need for MOPs to surface dollar values, improve processes, and validate ideas makes Data Science a natural ally. When MOPs and Data Science work together, revenue and lead generation become easier to predict, benchmark, and grow. But Data Scientists work their magic using emergent technologies that are expensive to deploy, and your CFO will only approve the budget for projects where the ROI makes sense. In any project proposal, focus on how the results can benefit the business and help Marketing boost ROI, and you’re likely to get the green light.


Marketing is now a data-driven discipline, where a top priority is to understand what generates revenue and drives growth. Data literacy is crucial for MOPs to handle data, structure their systems, and answer decisive business questions. Unfortunately, teams often lack the skills and resources to manipulate and turn data into an asset that generates value. Data Scientists are the ideal collaborators for MOPs to validate ideas and improve processes, but they’re hot commodities in every workplace.

When budgets are tight, it’s easy for C-Suite to overlook Marketing when approving spending for Data Science projects. So if you want the green light on a collaborative project with Data Science, show your CFO and CIO that the ROI makes sense.

We’ll guide you through that conversation in this Tough Talks Made Easy, with some help from Rachik Laouar. As the Head of Data Science at the Adecco Group, Rachik spent the last three years building a full-stack data team and making the business a predictable machine. Rachik contributes his personal views to this piece and does not represent the Adecco Group.


How Data Science enriches Marketing

One of the most persistent challenges Marketing teams face is proving their success. If you’re in a low-margin business in particular or otherwise facing cost strains, there’s extra pressure from your CFO to show your contributions to the bottom line.

Marketing as a space also has many “common sense” generalizations of best practice floating around, but the likes of “Never send an email on a Friday” don’t hold water for your business without evidence. Without the data or the know-how to interpret it correctly, your team is validating decisions and measuring success in the dark.

The need for MOPs to surface dollar values and make good judgement calls makes Data Science a natural ally. MOPs collects lots of data from campaigns, which Data Science can turn into detailed customer profiles and identify purchasing behaviours. Data professionals connect and map the entirety of your business’ data to spot patterns and understand how to optimise processes. Where Marketing generates leads, Data Scientists automate changes to the lead journey to trigger positive engagement behaviours. When MOPs and Data Science work together, revenue and lead generation become easier to predict, benchmark, and grow.


Collaborating with purpose

Data Science teams work their magic using emergent technologies, like machine learning and AI, which are expensive for companies to deploy. Collaborative time with Data Science and new tools, therefore, require a budget for development, which involves your CFO and CIO. Considering the costs, C-Suite’s looking to allocate Data Science resources only to teams that can justify the investment with impactful results. 

There are a few points you can make to leadership in response. By modelling the business end to end, Data Science can see what brings in the most revenue, and as one of the most commercially-minded teams, Marketing should be at the top of the list. The more you invest in making campaigns compelling in response to audience data, the more likely the business will win deals. In other words: investing in Marketing boosts the whole organisation.

You might want to work with Data Science to better a product’s audience and attract more customer segments to it. Alternatively, you might want to streamline operations through automation and cut processes to achieve better outcomes. Whatever your proposal, frame it to C-Suite with intended results and impact in mind. 

After all, you’re not running experiments for their own sake—you’re working with Data Science to help Marketing make or save more money than you spend, investing less per lead generated than you bring in. That’s the language your CFO and CIO speak. 

Leadership can be adverse to risk or expect quick results, which means your CFO or CIO might be hesitant to play the long game. A dose of reality: if you’re trying something new, you need time to ride it out, make sense of findings, and realise the benefits. Suggest running campaign experiments with small subsets of your audience first, as a proof of concept, to make the idea more palatable to a hesitant CFO. 

On the whole, explain the analysis and modelling you want to do, limitations included, and what you’re trying to achieve with revenue when testing certain actions. Focus on how the results can benefit the business, and if you can estimate the ROI at roughly 1.5-2x what you spend, you’re likely to move the dial in your favour.


Investing in success

MOPs and Data Science together can be a force of nature, making the wealth of data that Marketing collects actionable and steering better strategic decisions. Come to any conversation with leadership with a clear plan of action and a confident sense of how collaboration with Data Science can boost the bottom line, and you stand a good chance of getting the green light.

Need some help with data? Drop us a line to chat.