NEWS & EVENTS

Duncan McKay, business development manager at PBT Group The focus on digital transformation and being able to better understand customer needs are pressuring companies to embrace data as an integral component of the organisational culture. However, many...

Ashleigh Dickson, Business Development and Data Service Management at PBT Group A growing reliance for data to produce advantages that can support businesses to leapfrog ahead of any competitors continues to shine a bright spotlight on the Business Intelligence (BI)...

The Managed Solutions partnership – key to success
PBT Group thought leadership

It is no secret that the current economic environment is somewhat strained. As a result, businesses, regardless of size, are feeling pressure from all angles as economic conditions tighten, and with this, are shuffling processes and strategies to ensure they remain relevant and offer a distinct competitive differentiator.

As digital transformation progresses, technology is often considered to be the key to driving positive business change and sustainability, given the many opportunities technology can open up to business. This is attractive, and especially during tougher economic markets, when businesses need to leverage opportunity – and quickly – to push through.

However, there resides this consensus that technology investment is no simple task and in many instances is not a relatively cost effective one.

Enter Managed Solutions. When considering IT infrastructure investment, the managed solutions environment is seeing strong growth – being leveraged by business as a means to allow the business to invest in technology products, services and platforms, as and when they need to, to suit their growth needs. In fact, research notes that the global managed services market was valued at USD 166.8 billion in 2018, and it is expected to reach USD 319.5 billion by 2024.

The benefits

IT managed solutions and service platforms are gaining attention due to the benefits that can be reaped, which include:
• Cost – the provision of IT managed services can provide those IT-based services needed at a more competitive cost
• Access to experts – the services can be provided more efficiently by a managed solutions provider compared to what a business may be able to achieve in-house without significantly upscaling on talent and skills, which links back to costs
• Scalability – more flexibility can be provided in the nature of the services over what a business can achieve internally, and being able to upscale and downscale as required

The notable shifts

These same benefits and principles that apply to IT infrastructure, in today’s environment, also apply to the professional based managed solutions space. However, we are noticing a significant shift in the provision of such solutions – in that businesses can no longer afford to implement a professional based managed solutions project that would take 3 to 4 years to be completed and show a return on investment (ROI). With achieving a clear competitive edge being a critical goal, managed solutions projects are becoming shorter where the business needs to see the results within the same financial year.

Furthermore, given the pressures faced, businesses are now also looking for more agility and flexibility in how they provision their IT services, along with how they run their operations. This is resulting in the support function of managed solutions having evolved – and across all areas of the managed services stream.

Managed solutions and services platforms can no longer just be viewed or used as a support role – it’s no longer just about a provider going into a business and supporting an existing platform and solution – this is simply not sustainable. The demand today is much stronger.

With the need to grow the platform or solution, develop on it and ensure that it is keeping pace with what the business is demanding from it in support of the overall business objective and goal, the managed solutions function has to be viewed as a partnership, in order for it to be a consistent success. It is with this in mind that a business turning to managed solutions or services as a means to invest in technology trends, must do so by carefully selecting and working with the right partner.

And the right partner is one that can truly offer the business flexibility and is able to accommodate and support the business’ needs – that the business can focus on becoming more responsive to their market and achieve more in the way of growth than just being around to keep the lights on.

A fast-paced digitally driven world characterised by consistent technology evolution and change, is certainly an exciting space for business to operate in. Digital presents ample opportunities that were once impossible to even imagine, yet now worth exploring – not just to gain a competitive advantage, but for renewed business growth and plausible strategy.

And those involved in the data space have the privilege and excitement of being right in the middle of all this digital action. As digital evolves, the hunger for data grows as businesses seek to leverage its value as an asset for strategic growth.

One way of achieving this is to action your “reliable” data through the investment in data analytics. To my mind, the role data analytics is playing in business strategy is somewhat obvious. In fact, research forecasts that the global data analytics market will achieve a CAGR of 30.8 percent through 2023, reaching a market value of $77.64 billion by the end of the period.

Effectively analysing data can produce insights the business did not previously hold. Such insights can be critical to a business’s future planning, key decisions and overall sustainability and success. As such insights support a business to make strategic enhancements, as well as understand and therefore target customers better, resulting in improved overall outputs and likely higher retention rates. These are all of the good things we now know and have applied in our day-to-day business engagements with varying degrees of maturity. However, the challenge remains to gain the benefits from the investments made.

Whilst there are a variety of business processes, analytics models, governance and other factors that contribute to value of data analytics, the key to reaping such benefits does not lie in the analytics alone, but also in the quality of the data being analysed. Businesses must understand that the impact of data quality to the success of analytics is critical. If the integrity of the data being used is questionable, the end result may not target the right outcome, which can negatively impact the credibility of the analytics within the organisation and jeopardise the customer relationship. In the case of customer analytics, it’s fair to say that no customer today wants to be contacted about a possible offering that doesn’t meet a current need, or worse, about an offering from the same provider they already have that offering from. And while in some cases the data may not always be perfectly accurate, there are some important aspects that should be taken into consideration to ensure sound data quality for the purpose of analytics and to achieve the right value-based results.

The business data foundation
Data can come into a business from many different sources and in varied structures. Considering this and the fact that not all data is of sound quality, a business must have a solid data focused foundation in place, with the right technology infrastructure, that can effectively sort, manage, and store the good data, for the purpose of analysis. A strong data foundation also ensures that aspects such as data governance and security, related to data, are addressed in support of achieving quality data status.

Data quality tools and loading process
There are a number of tools within the data quality framework that can form part of a data strategy, that businesses can use to assess the quality of the data, and if it is indeed up to date and of good value. However, a consideration that must be addressed here is the data loading process – the time it takes for the data to be loaded from the source to the point that it is being served for the purpose of analytics. Data quality tools are only as effective as the actions that come out of the detections. The data quality tool will in most cases not fix data latency or loading issues but identify them to the relevant stakeholders.

To mitigate this risk to data quality, businesses need to ensure that there is monitoring and tracking around all the different levels of the data, through the whole ecosystem, and up until the data gets loaded into the data quality tools. This will ensure that the analytics that comes out of the data is effective and valuable. If there are gaps in the data, these will be identified within this process and the data sent back or removed, thus ensuring that the data ultimately used is of good quality and analytics is therefore comprehensive.

Timeframes
Of course, with the opportunities that analytics can provide, there is often an urgency to ensure that the analytics takes place within a quick timeframe. If there is a gap between the time the data is loaded into the system versus the timeframe the business needs to do the analytics, and if the analytics has to commence to meet business needs, there is the risk of the analytics occurring on data that is not yet fully ready, or on data not fully complete. To avoid this, a business must ensure the data timeframes are in place, and in line with the various business requirements and objectives.

It should be noted as a caveat that the above suggestions refer to analytics strategies and builds that consider larger data sets, such as predictive analytics for example, and do not refer to event-based analytics, where historical data quality might not be as important.

With that in mind and while certainly any business can, and will, find value and benefit from data analytics, it is important for analytics to take place on data that is of sound quality, to ensure viable and value driven results. Investing in analytics without investment into data quality is meaningless and won’t garner the desired returns the business will want to see from such an approach. Rather, taking the abovementioned aspects and suggestions into consideration will better support a data analytics strategy that derives real value for the business.