How data and analytics leaders are gaining the competitive edge

May 25, 2022

It’s clear that data and analytics are transforming industry competition, and while some businesses are accelerating at pace, many are yet to implement the necessary changes. In the latest McKinsey Global Survey, respondents believe that the changes data and analytics have created over the last few years have continued to grow. However, they also suggest that many businesses have reacted to this shift with one-off actions rather than implementing a long term plan.

Studies by McKinsey suggest many businesses are being relatively slow to respond to these transformations and potentially could find the gap between them and industry leaders extend further. Based on the report, companies with the most growth in revenue and earnings put a large amount of this increase down to data and analytics. Respondents from these businesses are far more likely to indicate data and analytics plans have supported an increase in earnings over the last few years.

What can other companies do to utilise data and analytics and follow others capitalising on the benefits of data and analytics? The most important factor is that these companies are implementing a long term data and analytics strategy and enforcing this as a core part of their workforce plan and culture. They ensure that high-quality data and modern technologies exist and can support further scaling.

In many industries, professionals believe data and analytics as a priority transforming the competitive landscape. 47% of respondents from the McKinsey survey believe data and analytics have changed the nature of competition in their sector over the last few years. While this may sound relatively low, it represents a 38% increase since the previous survey. When questioned about competitive changes, respondents point towards new analytics-focused businesses and the frequency of new companies emerging in this space. Despite the rise in competition, results suggest that most organisations still respond in an ad-hoc manner toward data and analytics plans.

Many industry professionals recognise that a lack of strategy for these areas will significantly impact future success. Over 20% of respondents believe having a data and analytics strategy is the number one reason for their success, an increase of 14% since the last survey by McKinsey.

While creating a strategy is essential, the survey results suggest that another vital factor driving success is delivering a data culture or creating measures that combine data and decision making. McKinsey interviewed a selection of businesses about their data culture and discovered that having employees use data consistently for decision making is critical for success.

Education is also a key factor, as developing a team with data and analytics skills is a top challenge to reaching a company’s objectives. Businesses have indicated a lack of company-wide education on data as a barrier to implementing new plans. Another aspect of creating a data culture is attracting and retaining the best talent, highlighted as a priority by employees at high-performing businesses. Similar to the previous survey, the biggest talent requirements are business users with analytic skills and a general need for more data professionals. While automation is growing, managing the data needed for these business changes is predominantly human-led.

Creating a data-driven culture requires technology that can support a business in utilising data and analytics. Establishing a solid data architecture enables companies to effectively collect and share data and ensure their employees can access and use information needed. It also allows for efficient delivery of high-level data quality, supporting data-based decision making.

The McKinsey survey suggests high-performing businesses have surpassed others in achieving their data and analytics plans and using both strategy and a solid data culture to extend the gap from other competitors. How can businesses improve the use of data and analytics and reduce the gap?

Improving the availability of data – the survey suggests how important it is to extract data from silos and place it in sophisticated analytics-based tools and allow decision-makers to have easier access to this information.

Recognising data as a product with genuine returns on investment – Business leaders often consider data as something supporting analytics and their decisions. Data should be viewed as an internal product shared across the group and integrated with performance, revenue, quality and other measures.

Be flexible toward data transformation plans – While high performing businesses have enforced a data culture, it’s critical to understand that even the best are yet to implement all of the suggested practices for data culture and have the room to go further. Rather than approaching this by attempting to tackle the gap with large-scale changes, businesses must focus on gradually evolving their data culture over time.

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Report states finance leaders see self-service data and analytics as vital for employee productivity

May 18, 2022

As CFOs explore ways to tackle the impact of inflation on margins, self-service analytics will be essential in driving employee productivity, according to a Gartner report. 

In December 2021, Gartner surveyed 400 finance leaders and discovered that over 50% saw self-service data and analytics as an essential driver of employee productivity. At least one in four saw it as vital for increasing business speed and agility. Self-service data analytics refers to technology and processes that finance users leverage with minimal involvement from IT departments. 

Alex Bant, chief of research in Gartner Finance, explains that two out of three finance leaders have raised their prices in response to inflation. Finding ways to improve productivity and efficiency rather than passing on inflationary costs to customers can create a critical long-term competitive advantage.

Advanced data and analytics and AI technologies generating high value and where investment is forecast to rise to include self-service data analytics, automated machine learning, cloud analytics, big data analytics and predictive analytics. 

Predictive analytics predicts a series of outcomes overtime or the distribution of an outcome that could occur for a specific event, using techniques like driver-based forecasting, time-series forecasting and simulation. Predictive analytics is one of the most popular use cases for finance executives automating their forecasting processes.

Bant explains that over 90% of finance leaders have increased their digital ambitions for 2022, but the same proportion is concerned about whether this development can continue due to slower growth, higher rates and the added pressure on profitability. Investment into the digital area, even as growth declines with be vital in determining the successful businesses of the future.

Big data and predictive analytics are considered critical technologies for generating higher revenue through improving products or services. Machine Learning and cloud analytics were viewed as the best solutions to improve cost efficiency.

The upcoming Gartner CFO and Finance Executive Conference will provide insights on the issues facing CFOs on June the 6th. The conference will deliver actionable insights for CFOs and their teams to support them on their digital journey and understand what makes a team successful. The Gartner Finance practice supports finance leaders meet their top priorities and delivering on vital initiatives that spread across finance and generate business impact.

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Managing the talent landscape in the SaaS industry

May 11, 2022

The simplicity of integrating and the option to pay as you go are just two factors that have encouraged the accelerated adoption of SaaS products. While there are concerns regarding security, data privacy and limitations to customising software, the underlying benefits of scaling and cost have led to large-scale adoption. The software products marketplace typically comprises two sections: Companies which began on-premise but have transitioned to mainly SaaS but retained an on-premise option for customers preferring this method. The second concerns newer businesses that are predominantly SaaS. This format began with companies like Salesforce and quickly became a preferred choice for traditional on-premises CRM software. There are also an increasingly large number of tech-focused companies essentially working as SaaS businesses. Companies in the consumer service industry like trip advisor, or companies in the finance scene, such as Stripe, are examples of this. There is an emerging talent war within the SaaS space, with traditional enterprise software companies that have moved to SaaS are now competing for top talent with leading businesses like Salesforce, and Workday, who are similarly competing with the large internet companies like Amazon and Google. 

Technical and executive positions at technology companies have never been in such high demand. This is likely to rise as businesses embrace automation, AI, machine learning and data intelligence. For software product companies, people capabilities are accelerating quickly as businesses and operating systems utilise cloud and SaaS services. Today’s software leaders need to work with more innovation and be capable of making quick real-time decisions, determining which products to use and improving what is working. A structured talent and engagement strategy is critical for software companies to attract the best professionals within the current industry. There are various sources to search, including new and pure-focused SaaS businesses, tech-enabled businesses, transitioned software companies and consulting firms. The booming industry environment has made it considerably more challenging to attract executives to a new platform, mainly due to the success in their existing roles. Generating interest from a candidate means the opportunity has to stand out, be captivating and specifically targeted at each individual. 

The recruitment challenge is particularly challenging for businesses in a transition phase, than those focusing on pure growth. For companies trying to recover and move on from legacy technologies, hiring a leading professional is critical to enable them to attract other high-level candidates to their business. 

The SaaS industry is growing at a considerable pace. Software service providers and tech-focused businesses compete for the same leaders and skillsets. Hiring managers and their search partners need to understand the software industry and where successful leaders are working and remain agile to how the industry is progressing. Creating the most compelling proposition to attract the best industry talent is critical.


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Why using the best available SaaS is critical in driving a business strategy

May 4, 2022

A hybrid multi-cloud approach is emerging as the preferred IT platform for implementing a business-focused strategy.

The priority of delivering a successful hybrid IT strategy is ensuring that it aligns with your business needs. This plan involves determining the most suitable on-premise systems and combining these with the most effective software-as-a-service (SaaS) applications available that meet the requirements of your organisation.

Adopting the best available SaaS technologies needn’t mean eliminating all non-cloud systems. Many businesses need these installed systems to support any plans for further innovation and digital transformation. Other challenging, resource-focused services may not be cloud-ready. These conditions require a hybrid approach, which enables cloud and non-cloud systems to work together so companies can operate various applications in non-cloud conditions while adopting cheaper and more efficient SaaS technology services.

Another vital consideration for creating the best hybrid multi-cloud strategy is ensuring the correct infrastructure model is applied when moving from legacy systems to a blend of SaaS-focused models.  

The costs associated with maintaining in-house systems must consider the operational costs of the buildings as well as the opportunity cost that comes with datacentre infrastructure. This is especially true when expanding a business or utilising new cloud technologies to accelerate transformation.

It’s important to take note of the possible inefficiencies that can occur with a data centre when factoring in these costs. Studies suggest that data centres can waste up to 90% of the energy used from the energy grid. Switching to a cloud-first datacentre model enables a business to take advantage of the economies of scale. It reduces a portion of that waste and can enable more efficient IT technology expenditures and allow for a quicker transition with the best available SaaS technologies.

Combining a hybrid IT strategy with a structured implementation plan allows infrastructure to be scaled, improves enterprise agility and enhances transformation by using a good mix of on-premise and SaaS technologies.

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