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Whose role is it anyway? Why finance underpins data-led digital transformation

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Joe DosSantos, Chief Data and Information Officer, Qlik

Digital transformation is no longer an aspiration for tomorrow but a necessity of today. However, amid a rush of post-pandemic digitalization, one essential element is too often swept aside. That is how modernized data strategies can deliver up-to-date financial performance insights that drive real-time decisions and action. How can a Chief Finance Officer (CFO) transform the finance function to provide rich analysis that impacts business performance?

Finance’s ability to support today’s agile, data-driven organizations is imperative. However, according to McKinsey, less than half of CFOs play a leading role in driving enterprise-wide transformation.

As a data-driven organization we knew that finance data modernization was key to our growth ambitions. As Chief Data Officer (CDO), I worked closely with Qlik’s CFO to modernize our data, strategy and architecture, integrating finance and business data to transform Qlik into an agile, data-driven organization. In ensuring finance can harness data and digital to become an essential lever for driving the business forward, our journey has produced learnings that others may find helpful.

People first

Before getting to master data management, analytics and artificial intelligence (AI), it is essential to understand the skill set that finance professionals need to play their role in modernization. Data literacy is vital; having the ability to understand data and translate it into recommendations and actions for the business. Increasingly, finance teams need to understand the principles of master data, data flow and how AI and machine learning can contribute to their decision-making process. Armed with the right data and insights, finance can better interact with broader business stakeholders in this new paradigm.

For example, my first order of business was to request our executive team to dedicate one person from their function as the go-to data champion, to speak on behalf of that group and uncover strategic drivers. Then we embarked upon a value engineering exercise to truly triangulate on the value that each of these different use cases could create, and then to focus on cross-functional issues.

If you want to drive value across the organization, you need to get people working together to become laser focused on strategic priorities. In our case, that was understanding our customer base to support retention and satisfaction, underpinned by financial metrics. By going through this exercise and involving the whole organization, the finance function has gone from number crunching to becoming a true business partner.

Finance’s insatiable appetite for data

From there, we start by going back to what seems like a basic. Just as we are all used to opening up a mobile banking app and seeing our balance, the CFO wants to know the organization’s cash position in real-time. Especially given current global currency fluctuations, it is crucial to have a clear picture to inform decisions made in the moment.

Every day organizations make micro-decisions that affect the customer, and it is no longer viable to make those decisions based on disparate data from weeks or months ago. This requires real-time data within a comprehensive master data strategy.

Finance has an insatiable desire for data, and can draw on myriad sources, including ERP, CRM, supply chain management and other dispersed systems. Data sources are constantly evolving, and finance teams must be able to quickly harness larger and more complex data sets that deliver actionable insights that support the business.

As McKinsey highlights, ‘Owing to its central role, the finance function is uniquely positioned to help define the master data strategy for the enterprise. To support the business – whether through more nuanced financial-scenario planning, insight into how to better manage liquidity, or improved guidance on where to best deploy assets – finance must be able to quickly marshal high-quality, trusted data.’

Modernizing our finance operations started by moving all data to the cloud, using our Qlik SaaS platform to address size and scale requirements. From here, it was crucial to address data usability and reusability. For example, determining how exactly we would calculate EBITDA or recurring revenue so that we had an array of replicable, reusable metrics to deliver in-the-moment insight.

Anchoring sophisticated data science in hard metrics

Formalizing definitions combined with a cloud data strategy set the foundation to be able to answer vital questions quickly. It goes further, however, opening up opportunities to leverage technology to automate, innovate and to monetize, as well as providing the scaffolding for more sophisticated data science approaches, including our use of AI.

For example, we can dissect different data segmentations that give a real picture of current performance, but that also indicate what is needed to improve future performance, whether in terms of months, quarters or years. The more value drivers connected across the business, the more transparency and insight you gain into the impact of one KPI relative to the overall performance, and this can prove incredibly powerful.

Data science helps us understand the behavioral patterns of people, their product usage, buying cycles, for example. But the key to harnessing this insight is making sure it is anchored to financial metrics. Again, this is echoed by McKinsey’s analysis; ‘Leaders can help their teams by ensuring that requests for more information are grounded in a solid understanding of an agreed-upon set of drivers of business financial performance’.

To achieve a high retention rate, we must access the metrics that drive it. That means using data science to understand customer behavior, ensuring the right, accessible analytics to measure the impact on the bottom line of using this insight. In that respect, today’s data modernization strategy uses finance as a lever for the rest of the organization to meet goals, charting a path of clarity that traverses marketing, sales, and customer success.

Future growth rooted in today’s data

Adopting a cloud-based, master-data strategy driven through finance, and supported by collaboration across the organization, we have transformed Qlik to become truly agile. We needed to better understand how to please customers and grow our revenue over time and that understanding is rooted in financial metrics.

By modernizing infrastructure finance teams can work with data in the moment, partnering with other lines of business to drive fact-based decision-making. As a result, finance is now instrumental in ensuring the business uses data to keep their eyes on the future, yet with feet firmly grounded to drive positive change today.

 

Finance

Taxing times for online marketplaces? Operators must act now to avoid losing sellers

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By Niall Kiernan, Senior Director of Product Marketing, Vertex

 

In today’s digital landscape, online marketplaces are an enabler for many businesses to achieve their growth ambitions. From Amazon to eBay, Etsy to Vinted, businesses of all sizes are now utilising online marketplaces, and recent years has seen exponential growth in this area. Numerous factors, including the proliferation of mobile devices and widespread availability of high-speed internet, have resulted in this escalation. Combined with consumer demand for convenience, along with the impact of the pandemic, the success of online marketplaces can be seen in the numbers. In 2021, retail eCommerce sales amounted to approximately US$ 5.2 trillion worldwide. This figure is forecast to reach US$8.1 trillion dollars by 2026.

It is clear that online marketplaces are a vital source for businesses to continue to flourish but there are still major roadblocks which can hinder a business’ efforts to capitalise on the booming sector. According to research commissioned by Vertex, which surveyed 479 finance professionals globally, seven out of ten sellers using marketplaces to trade online believe that indirect tax challenges could deter them from using them again in the future.

The complexity of ensuring a frictionless eCommerce experience

Whilst over half of respondents in the survey agreed that marketplaces are getting easier to use as a sales channel, ensuring that both operators and sellers can enjoy a frictionless experience is one of the biggest challenges in the space. Respondents indicated that they are looking for more support and guidance on issues including: how to ensure transactions and the transfer of money can be more seamless (65%), tax liabilities (64%), and compliant invoicing (63%). But what are some of the specific roadblocks both marketplace operators and sellers are experiencing?

  1. The cross-border trade conundrum

85% of marketplace operators surveyed indicated that they are looking to increase their seller base, however there are numerous tax complications when trade crosses borders. Four out of seven operators stated they have struggled to manage tax liabilities and tax complexities around seller shipping locations. Online marketplaces are very much a global affair, with cross-border transactions being the norm.

The difficulty here is that both operators and sellers must comply with the different tax regimes of the countries they operate in, which can be a complex and burdensome process. Seller respondents reported a wide range of issues when they sell through marketplaces, including balancing their tax liabilities and knowing where and when they are liable for tax.

  1. Complexities in every step of a transaction

Dig beneath the surface and the process of a transaction is much more complex than initially meets the eye. From listing fees to shipping and handling charges, or the previously mentioned cross-border trade complexities, every step in the transaction process brings multiple challenges to both the operators and sellers themselves.

45% of sellers surveyed want their marketplace operators to improve the process of finance and tax automation to overcome these barriers, but of the operators, only 56% manage all tax liabilities on their seller’s behalf. If marketplace operators want to ensure they have a healthy population of sellers, this figure needs to increase.

Tax technology for a trouble-free tomorrow

Although there are clear and significant indirect tax challenges for online marketplaces, the space remains an attractive channel for businesses to achieve their growth ambitions. 81% of businesses are taking advantage of online marketplaces to attract new customers and sell into more countries and upon further inspection, they attribute this expansion into marketplaces to reach a wider geographical market (57%), to being more competitive (50%) and to tap into cross-border sales opportunities (48%). It’s clear that sellers are wanting to utilise online marketplaces to expand their customer base globally and if operators want to increase their seller base and take advantage of the growing demand for this, and 85% of those surveyed do, then they need to ensure that their platforms offer a seamless experience for their sellers.

By investing in an end to end tax management solution which can handle all types of indirect tax requirements, you will be able to support sellers on their own individual growth journeys. In addition, you can rest assured that it will also enable them to feel confident that their chosen platforms can meet all the indirect tax requirements as they increase their cross-border sales.

To learn more about the taxing times for the marketplace and seller relationship, download the latest report by Vertex.

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Unlocking the Power of Data: Revolutionising Business Success in the Financial Services Sector

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Suki Dhuphar, Head of EMEA, Tamr

 

The financial services (FS) sector operates within an immensely data-abundant landscape. But it’s well-known that many organisations in the sector struggle to make data-driven decisions because they lack access to the right data to make decisions at the right time.

As the sector strives for a data-driven approach, companies focus on democratising data, granting non-technical users the ability to work with and leverage data for informed decision-making. However, dirty data, riddled with errors and inconsistencies, can lead to flawed analytics and decision-making. Siloed data across departments like Marketing, Sales, Operations, or R&D exacerbates this issue. Breaking down these barriers is essential for effective data democratisation and achieving accurate insights for decision-making.

An antidote to dirty, disconnected data

Overcoming the challenges presented by dirty, disconnected data is not a new problem. But, there are new solutions – such as shifting strategies to focus on data products – which are proven to deliver great results. But, what is a data product?

Data products are high-quality, accessible datasets that organisations use to solve business challenges. Data products are comprehensive, clean, and continuously updated. They make data tangible to serve specific purposes defined by consumers and provide value because they are easy to find and use. For example, an investment firm can benefit from data products to gain insights into market trends and attract more capital. These offer a scalable solution for connecting alternative data sources, providing accurate and continuously updated views of portfolio companies. Using machine learning (ML) based technology enables the data product to adapt to new data sources, giving a firm’s partners confidence in their investment decisions.

Suki Dhuphar

But, before companies can reap the benefits of data products, the development of a robust data product strategy is a must.

Where to begin?

Prior to embarking on a data product strategy, it is imperative to establish clear-cut objectives that align with your organisation’s overarching business goals. Taking an incremental approach enables you to make a real impact against a specific objective – such as streamlining operations to enhance cost efficiency or reshaping business portfolios to drive growth – by starting with a more manageable goal and then building upon it as the use case is proved. For companies that find themselves uncertain about where to begin their move to data products, tackling your customer data is a good place to start for some quick wins to increase the success of the customer experience programmes.

Getting a good grasp on data

Once an objective is in place, it’s time for an organisation to assess its capabilities for executing the data product strategy. To do this, you need to dig into the nitty-gritty details like where the data is, how accurate and complete it is, how often it gets updated, and how well it’s integrated across different departments. This will give a solid grasp of the actual quality of the data and help allocate resources more efficiently. At this stage, you should also think about which stakeholders from across the business from leadership to IT will need to be involved in the process and how.

Once that’s covered, you can start putting together a skilled team and assigning responsibilities to kick-off the creation and management of a comprehensive data platform that spans all relevant departments. This process also helps spot any gaps early on, so you can focus on targeted initiatives.

Identifying the problem you will solve

Now let’s move on to the next step in our data product strategy. Here we need to identify a specific problem or challenge that is commonly faced in your organisation. It’s likely that leaders in different departments, like R&D or procurement, encounter obstacles that hinder their objectives that could be overcome with better insight and information. By defining a clear use case, you will build a real solution to a challenge they are facing rather than a data product for the sake of having data. This will be an impactful case study for your entire organisation to understand the potential benefits of data products and increase appetite for future projects.

Getting buy-in from the business

Once you have identified the problem you want to solve, you need to secure the funding, support, and resources to move the project ahead. To do that, you must present a practical roadmap that shows how you will quickly deliver value. You should also showcase how to improve it over time once the initial use case is proven.

The plan should map how you will measure success effectively with specific indicators (such as KPIs) that are closely tied to business goals. These indicators will give you a benchmark of what success looks like so you can clearly show when you’ve delivered it.

Getting the most out of your data product

Once you’ve got the green light – and the funds – it’s time to put your plan into action by creating a basic version of your data product, also known as a minimum viable data product (MVDP). By starting small and gradually enhancing with each new release you are putting yourself in the best stead to encourage adoption and also (coming back to our iterative approach) help you secure more resources and funding down the line.

To make the most of your data product, it’s essential to tap into the knowledge and experience of business partners as they know how to make the most of the data product and integrate it into existing workflows. Additionally, collecting feedback and using it to improve future releases will bring even more value to end users in the business and, in turn, your customers.

Unlocking the power of data (products)

It’s crucial for companies in FS to make the most of the huge amount of data they have at their disposal. It simply doesn’t make sense to leave this data tapped and not use it to solve real challenges for end users in the business and, in turn, improve the customer experience! By adopting effective strategies for data products, FS organisations can start to maximise the incredible value of their data.

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