Blog - 14 Jul 2021
5 minute read
Data Science & Analytics

Blog

Data & analytics for many mid-market organisations can have a transformative impact. However, beyond this high-level statement it can be difficult to understand exactly what the possibilities are, or where they are buried. It’s time to have a data conversation with Ascent.

data & analytics, data conversation, data science, data-driven, mid-market, data transformation

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2021-07-13T23:00:00Z

Brilliant data conversations with mid-market businesses.

Chief Data Scientist, Rich Pugh looks at the role that data has to play in the success of mid-market organisations.

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Data Science & Analytics

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In my role, I am lucky enough to work with a broad range of customers across different markets, helping them to deliver value from data.

More recently, I’ve seen a trend in conversations with mid-market businesses who are looking to mature their data approach. For me, this represents an exciting shift in thinking that clearly positions data (and its potential) as an understood accelerator of growth.

‘Mid-market’ vs ‘data immature’

Over the last 25 years I’ve worked largely with Enterprise customers across ‘data mature’ sectors such as pharmaceutical, finance, insurance and government. These conversations are about a gradual move to more proactive uses of data, including discussions around the changes required to really make that happen at scale, while delivering high-value solutions quickly (often as a driver for investment cases to modernise legacy technical estates). It’s a conversation I know well, and I’ve been really fortunate to have worked on data transformations with some of the largest organisations in the world.

At the other end of the scale, I really love to work with startups. Unencumbered by legacy tech and thinking, startups are able to innovate quickly to explore many avenues. A huge benefit to a startup in this era is the ability to root its operations in more data-driven thinking and technical advances like DevOps, Cloud and microservices architecture as well as novel machine learning methods. This allows them to scale more quickly, shortening the time to compete with established partners and cause disruption.

But what I’ve noticed, over the last 5 years in particular, is the increase in conversations I’m having with companies in the middle of the spectrum. And because typically the top end of my reference scale is Enterprise and the lower end of the scale is start-ups, I found myself referring to the in-between segment as ‘mid-market’. But recently I have rethought this perspective and realised it’s a shorthand I need to stop using. Certainly size is a factor, but a more complete definition would be ‘established companies from relatively data immature industries’. Recent examples of customers this would include:

  • A Premier League football team

  • A leading tool hiring solutions company

  • A large recruitment firm

  • A traditional ‘bricks and mortar’ retailer

  • A progressive brewery

  • A retailer of beauty products

Why the data conversation?

If we consider this list, then you can see why ‘mid-market’ really isn’t the right term to use. These customers represent a range of annual revenues of (say) £50m to £7bn. The thing that connects these customers is not size - it is the quality of the conversation and the way they are looking at the data opportunity. Each of these customers can be defined as an organisation:

  • That had not historically seen data and analytics as a direct source of value

  • Without an internal Analytics team or Data Science function

  • Looking to leverage data to drive their business outcomes

  • That doesn’t necessarily yet have a full picture of how data will impact their business.

Because of these factors, the conversations I’m having are (quite frankly) brilliant. They are data conversations as they are meant to be – focused on understanding the potential with organisations who are open to explore opportunities to accelerate. Of course, without mature internal data teams, they sometimes start the conversation in the wrong place. But early questions such as ’can we do some AI?’ or ‘what does our data tell us?’ quickly get reframed into a good discussion about how data can drive positive change and generate value.

Where do we start?

An interesting thing I’ve heard early in these conversations (albeit from a minority of customers) is the idea that ‘we don’t do data’. Just to be clear: you do. Every established organisation (or, perhaps, every organisation full stop), ‘does data’. You can’t not. If you employ people, or invoice customers, or have a stock list… you are 100% ‘doing data’. This is an important mindset to start with. However, a good question to pose early on is ‘what role does data play in your organisation, and your success?’.

For many customers in this area, data is seen simply as a by-product of the businesses operation as opposed to something that guides it. For some, data is seen as something that is a burdensome overhead on the business. A chore. A penalty to pay for running the business. For others, data is the thing that lives in the spreadsheets, or that people have to wrangle to generate that regular report.

Very often, customers in this space have some sort of data platform (e.g. a data warehouse) and the ability to perform some level of reporting. However, a lack of data governance and ownership can lead to challenges in the business around data quality and interpretability. This in turn leads to challenges around reporting, regardless of whether the reporting team is a centralised BI function or ad-hoc Excel / dashboard magicians living in business areas. This can lead to long lead times for non-standard (and sometimes standard!) reporting - and can lead to issues around quality that fundamentally undermines the trust in data.

Of course, the situation can vary, but if you recognise any of this – you are not alone!

Where do we go from here?

So if this is the starting point – what’s the destination? For many organisations, there is a broad understanding that data can have a transformative impact. There’s definitely gold in them thar hills! However, beyond this high-level statement it can be difficult to understand exactly what the possibilities are, or where they are buried.

The best way to have a great conversation about data is to absolutely not talk about data. That is why brilliant early conversations focus on an organisations' business aspirations. How do they see themselves? What makes them different? Conversations around an organisations' purpose and their motivations can really help to create a clear picture of where they want to go and how they want to be seen. At this point, we can look at how data can help to deliver on these business objectives and plan a roadmap to success!

Bringing data to the mid-market' is a data conversation by Ascent’s Chief Data Scientist, Rich Pugh (DataIQ 100) and covers all you need to know about data strategy, objective setting and implementation.

Rich Pugh

Chief Data Scientist

Ascent

As Chief Data Scientist at Ascent, Rich is passionate about delivering pragmatic advice to leading organisations on data-driven transformation and building successful data science teams.

With more than 20 years’ experience helping companies create value from data, Rich has worked across a variety of industries, helping businesses around the world increase profit margins, solve operational challenges and delight their customers.

Rich is a strong believer that there is nothing analytics can’t do and strives to help organisations leverage the power of their data.

Rich Pugh

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