Data management: store and share "Product people - Product managers, product designers, UX designers, UX researchers, Business analysts, developers, makers & entrepreneurs August 08 2022 False data driven culture, Data driven products, data management, data visualisation, Prioritised Members' Content, Stakeholder Management, Mind the Product Mind the Product Ltd 1621 Product Management 6.484

Data management: store and share

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In the second of this two-part series on data management we look at how the data you collect should be presented and shared with stakeholders and why getting this right is important. We also look at how you can use data to make better roadmap decisions and how data can help with stakeholder management.

The first part, Data management: collect and organise, should help you to understand what being data driven really means, how data product management is different from product management, and good practice for data collection and organisation.

TL;DR
Keep the presentation of data simple
Think about the story you’re trying to tell
Use data visualisation tools and tec…

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In the second of this two-part series on data management we look at how the data you collect should be presented and shared with stakeholders and why getting this right is important. We also look at how you can use data to make better roadmap decisions and how data can help with stakeholder management. The first part, Data management: collect and organise, should help you to understand what being data driven really means, how data product management is different from product management, and good practice for data collection and organisation. TL;DR Keep the presentation of data simple Think about the story you’re trying to tell Use data visualisation tools and techniques to boost immediacy Remember that stakeholders will have a different perspective on what’s important Get to know them and understand their priorities so that you can share data appropriately Data can help you make better roadmap decisions, but remember you may need to strike a balance between being customer-informed and being vision-informed

How should the data you collect be presented?

Data visualisation is key. As Alison Whitehouse, Product and Organisational Agility Consultant at PA Consulting says,  it should always be consistent, regular, and as simple as possible regardless of who you present to: “Using data to inform your decisions or bolster your argument on a given product strategy is what sorts the heavyweight from the lightweight product managers,” she comments. Amplitude’s Chief Product Officer Justin Bauer advises thinking about the story you’re trying to tell and keeping it simple. He says: “Which data or metrics actually show ROI and business impact? It also helps to regularly present and share data with stakeholders so that they can become more familiar with it. Whenever possible, integrate data into things like weekly syncs, stand-ups, and all-hands meetings.” There’s a huge amount of resources available online to guide you through effective data presentation. This Harvard Business Review article, for example, Present your data like a pro runs through some useful tips for helping you to deliver maximum impact. Additionally, this fun session from #mtpEngage Hamburg, Let’s Engage – Live Data Visualisation at MTP Engage Hamburg 2018, adroitly illustrates the power of effective data visualisation.

How should data be shared with stakeholders?

Again, keep it simple should be your mantra when sharing data with stakeholders, says Amplitude’s Justin Bauer: “If it’s too difficult to pull insights, or the insights you do have are highly complex, you’ll end up losing the confidence of your stakeholders if they can’t trust all the behind-the-scenes analysis.” John Little, Vice President of Product at testing platform Centercode points out that while the product manager may have a vision for the product and be able to get others on board, each stakeholder will have a different perspective on what is important to the product and company. Product managers need to understand each stakeholder’s priorities and connect them to the vision of the product. It’s easier to work one-to-one with stakeholders, John finds: “Product managers have a lot of responsibility, but often not a lot of authority. It's best to work one-on-one with individuals when starting a new product engagement - not multi-department workgroups. By working one-on-one with each team you're able to build a relationship and really understand what that team needs to succeed while avoiding crowded group dynamics or group think. Once you understand each department’s stakeholders you’ll be able to craft the data to best support each team and keep everyone on target.”

Why is this important?

There’s a persistent idea that using data removes politics and interpersonal communication, says Matt LeMay, Partner at Sudden Compass, but it’s mistaken. “It’s still people interpreting data,” he says, “and people can find all kinds of ways to interpret, and misinterpret what you share.” This effort to understand stakeholders is significant in other ways too. Matt comments that while product managers look to deliver results for the business, the best product managers understand that everything is a trade-off. A product manager’s job is never to convince stakeholders, it's to inform stakeholders, he says. “You want to use data to help them understand the trade-offs - the pluses and the minuses, all the things that could go right, and where they could go wrong.” Data is often framed as a tool of persuasion, says Matt, and he’s seen lots of product managers try to use data to make the case for something they want to do. (There’s nothing new in this, Darrell Huff’s famous book, How to lie with statistics, was first published in 1954.) He says: “When people come to me saying the data is clearly telling us to do this one thing. I am sceptical, because it's very rare that there is a clear, correct option.” Arguing for only one potential path forward doesn’t reflect reality, he believes. Product managers need to be able to take stakeholder views, understand what the company is trying to accomplish and connect that to a real-world context, he says. Good product management, he says, “lives in optionality. If you have to present multiple options with trade-offs, you can still live and it's harder to lie”.

How can you use data to make better roadmap decisions?

Data can help you make better roadmap decisions. This may seem obvious but a business, particularly in its early stages, can overlook the value of its data in favour of a vision. This McKinsey article, Capturing value from your customer data, explains how businesses only ever use a fraction of the data they possess. It looks at the strategic importance of customer data and quotes Gallup research that finds that organisations that leverage customer behavioural insights outperform peers by 85% in sales growth and more than 25% in gross margin. In this ProductTank San Francisco talk When A/B Tests Aren’t Enough, Scott Castle, Chief Strategy Officer at Sisense, talks about blending different data sources to help build up an understanding of what customers are doing, and to understand whether his product teams are building the right things to create customer success. That said, there’s a balance to be struck. In this episode of The Product Experience podcast, Product roadmaps vs data, Jeremy Levy, CEO at Indicative, talks about how he leverages customer data to inform his product roadmap. He talks about how important it is for a roadmap to be customer-informed as well as vision-informed, and how roadmaps don’t need to be perfect, but should keep being updated to reflect what you know. In this blog post, Product Roadmap Best Practice – 6 things to avoid!, Janna Bastow, CEO of roadmap software vendor ProdPad, comments that it’s possible to be too data-driven. She thinks that A/B testing can end up as an expensive way to disagree, and says that while all these little tests might seem like good work, they don’t bring results. Better to step back and look at the bigger picture. John Little also points out that if you’re entering a new market, have a new product, or have joined a company that’s not data driven, you might not have the data to start with. He says: “Let yourself know that it’s okay, and make a decision based on all the data that is available. Getting stuck in analysis mode and not being able to move your product forward can happen just as fast with too little data as it does with too much.”

How can you leverage data flow throughout an entire product lifecycle?

Alison Whitehouse comments that you need a range of data points - tooling where you can see how your delivery teams are delivering against the roadmap, outputs from customer sessions such as digital diaries, insights from customer journey touchpoint visualisations where you can see where customers drop out of a journey for example, and so on. They should enable the product manager to gain both a deep understanding of your customer and the product development process, she says.

But data won’t do your job for you

It may be very tempting, and perhaps easy, to let your product decisions be ruled by the data you have in front of you. But you should always bear in mind that data will not do your job for you. Matt LeMay points to a TED talk his business partner Trisha Wang gave a few years ago, The human insights missing from big data. In it Trisha tells the story of her time as a researcher with Nokia, then the world’s dominant mobile phone manufacturer, in 2009. She spent a lot of time in China getting to know the informal economy. She could see big changes afoot among low-income Chinese people, and that the ads that enticed them the most were the ones for iPhones. Trisha could see that even the poorest people in China would want a smartphone and that they would do almost anything to get one. Nokia was not convinced because its data told them a different story and its management chose not to follow her advice. As we all know, Nokia missed the smartphone wave and its failing phone business was sold to Microsoft a few years later. Says Matt: “Data will not tell you what the single right or obvious thing to do is. It can help you to understand the trade-offs and decisions you're making, and can help you adjust course as you go about making those decisions. But data will not make your decisions for you.” Want to share your thoughts on this article? Use Circle—our members’ discussion platform exclusive to MTP members—to drive the discussion and share your product experiences.

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