In today's business landscape, data has become more than just a technical asset – it's a strategic driver of business growth and financial performance. We sat down with Jonathan Teale, intive’s experienced finance and data strategy expert, to discuss how forward-thinking organizations are leveraging data to create competitive advantage and drive bottom-line results.
Looking at successful companies today, how do you see them using data to drive business growth?
Jonathan: I see data, particularly from a finance point of view, as the solid foundation on which you can drive business decisions. In companies without a joined-up data strategy, there's no proof of anything, and people spend substantial time and effort on tasks that should be automated or streamlined.
A good, solid data foundation enables a business to concentrate on strategic matters. It's like the foundation of a house – it enables growth by providing the solid platform on which business leaders can rely. Business leaders shouldn't be looking at spreadsheets; they should be making decisions on growth and strategy. If you have a solid foundation, you can stick the roof on, but you can't put on a roof when there's no house.
That's an interesting analogy. Can you share some real differences you've observed between companies that get data right versus those that struggle?
Jonathan: It depends on different sectors. A retail and wholesale company will rely heavily on inventory data – if you don't have a good joined-up inventory strategy, you either don't have stock to sell or you've got too much and things go to waste. This directly impacts competitive advantage.
Similarly, with good CRM data, your operational side becomes so much more efficient. I've seen organizations that could either leverage their customers 1000% better or significantly reduce department size through improved efficiency. Good data not only leads to better customer engagement but also makes for a leaner business because you don't have people doing work that the data should be doing for you.
When you talk about data-driven organizations, what would you say are the foundational elements they all share?
Jonathan: You need a solid base on which you can build. It comes down to your business KPIs. You decide as a business: what do we want to measure? What do we want to drive our business by? That in turn determines what sets of data you require.
For example, a mining company digging materials from the ground isn't going to be as concerned with customer satisfaction scores or marketing data, but might be very involved in warehousing and production cost analysis. The pillars should align with your business KPIs. If your KPIs aren't joined up to your data, there are no pillars. It's about determining what you need from your KPIs in order to build an effective data strategy.
Many companies struggle with connecting their various systems like ERP, CRM, and finance platforms. What's making this so difficult for them?
Jonathan: Each company has its own unique challenges, but I find the biggest challenge is actually the people, culture, and the program of change required. As they say, you can't make a silk purse out of a pig's ear – if people don't engage with the data strategy, it won't succeed.
This is particularly true with systems like CRM where there's a lot of process associated with the data. It's not just software; it's a set of end-to-end processes. If the leadership team doesn't fully buy into the data processes and the change program, it often fails. You can spend millions on Workday, SAP, or Salesforce, but if people don't follow the program, you won't see results.
Cultural differences also play a major role, especially in multinational companies. How people work can be completely different across regions, with different ways of communicating and different social norms. So along with leadership buy-in, you need cross-cultural and cross-departmental commitment to the change.
That's fascinating about the human element. How about on the metrics side. How can companies ensure their KPIs actually mean something?
Jonathan: You need to review them on a periodic basis. If you're starting out, you could use AI tools to identify best practice KPIs for your specific business type and size. For instance, what are the best practice KPIs for an inventory-based wholesale business with $100 million turnover in a single country?
The answers will often be fairly simple sets of KPIs that are standard for your industry. A company in IT services will have a completely different set of KPIs compared to a retailer. The key is ensuring they're aligned with your specific business needs and reviewing them regularly.
Everyone's talking about AI and real-time analytics these days. Are they game-changers or just buzzwords?
Jonathan: The need for real-time analytics depends entirely on your industry. If you're an airport, you need real-time analytics for flight data. If you're a large supermarket chain, you need real-time data on inventory like whether you're selling out of certain products. However, if you're an IT services company or a wholesaler of widgets, you probably don't need that kind of real-time capability for your internal operations.
AI has certainly made advances in real-time analytics much easier to implement. But while AI is great at building analytical tools, it might not deliver exactly what you need. You still need people who understand the metrics and your business context.
The pace of change in AI is quite remarkable. Over the next couple of years, companies that use AI to their advantage in everyday practices won't necessarily be the only ones who succeed, but they will likely have lower cost bases.
Regarding compliance and regulatory issues around AI, it's currently a complete Wild West. There are companies suing others for training models on copyrighted data, and many unresolved legal questions. The compliance issues around AI are numerous and evolving.
With technology changing so quickly, how do you build a data strategy that won't be obsolete next year?
Jonathan: Some of it depends on your platform. The platforms we have for data now, like Microsoft Fabric which we use extensively, make it much quicker to implement changes than ever before. People who aren't expert coders can achieve significant results.
However, flexibility and quality don't always go hand in hand. Your business processes should drive the data strategy, not the other way around. Once your data strategy is aligned with your business processes, it shouldn't need to change frequently. Business processes don't typically change drastically, so your data strategy, once properly implemented, should remain relatively stable.
If you're constantly changing your data approach, people don't know what they're doing. A solid data strategy is like the engine in a car – you can't have a gold-plated Rolls Royce with a subpar engine. With solid business processes and data strategy, you can focus on generating top-line growth while knowing your data foundation is taken care of.
It's a hygiene factor – not necessarily exciting, but necessary so you can concentrate on the strategic elements of your business. Get the basics right with your business processes and KPIs, then let the sales team focus on generating revenue.
The Power of Strong Data Foundations
As Jonathan Teale has illustrated throughout this conversation, a robust data strategy isn't merely a technical consideration – it's a business imperative that drives financial performance. Organizations that build solid data foundations can shift their focus from operational firefighting to strategic decision-making that propels growth.
Interested in exploring how technology can help solve your business challenges? Visit our portfolio of digital solutions across various industries or reach out to discuss potential collaboration opportunities. Let's connect and explore how we can help your organization thrive in today's data-driven world.
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