Insights & Ideas

Three Steps to Achieving a Return-Before-Investment with Cloud Analytics

Why On-Premise Business Intelligence And Traditional Return-on-Investment Models Are Costing Your Company Millions

Preface from Jeffrey Kaplan of THINKstrategies

The world is changing and organisations of all sizes need new management tools to respond to today’s escalating demands.

Organisations across nearly every industry sector are facing unprecedented macro-market forces which are driving them to seek new and more effective business intelligence (BI) and analytics tools to achieve their corporate objectives. These forces include:

  • Continuing economic uncertainty
  • Escalating market competition
  • Changing workplace dynamics
  • Rising end-user expectations

In order to compete in this atmosphere, organisations need to better understand customer preferences and behaviour to focus their operations properly. They must also be able to collect and disseminate this information more quickly across a more dispersed workforce and supply-chain of business partners.

Traditional BI systems were not designed to respond to today’s realities. Instead, they were built to be highly centralised resources that could only be accessed by a small group of skilled data analysts or a limited set of corporate executives. Deploying and managing traditional BI systems has been fraught with challenges and seldom achieve the return-on-investment (ROI) organisations anticipated despite significant capital costs and ongoing staffing needs. As a consequence, departmental managers and customer-facing end-users have lacked the information and insight they need to make important day-to-day decisions that can impact the business.

These trends are driving a growing number of organisations to adopt a new generation of ‘on-demand’, web-based, Software-as-a-Service (SaaS), cloud BI alternatives that are easier to deploy and administer, and more flexible and economical to utilise. As a result, today’s cloud BI solutions are producing immediate returns and measurable business benefits for organisations of all sizes across every industry.

Therefore, THINKstrategies believes that organisations can not only quickly benefit from today’s cloud BI solutions; they will require these solutions in order to remain competitive in the years to come.

Fortunately, organisations of all sizes can now adopt new cloud-based solutions which enable new approaches and models to assess their business investments, such as Return-Before-Investment. These cloud-based alternatives have created new opportunities for executives to better manage their operations so they more cost-effectively can achieve their corporate objectives.

Jeffrey Kaplan

Managing Director

THINKstrategies

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Three Steps to Achieving a Return-Before-Investment with Cloud Analytics

Cloud computing is unleashing massive value across the enterprise IT ecosystem. So disruptive is this new business model that traditional on-premise tools used by chief finance and information officers to assess technology investments such as Return-on-Investment (ROI) have now become completely outdated.

Instead, Return-Before-Investment (RBI) has emerged as the new metric for measuring the accelerated value that the cloud – and, in particular, cloud analytics, enables for leading companies. It offers them a far cheaper, simpler and more broadly applicable alternative to the legacy models of enterprise computing.

The driving force behind the growing adoption of RBI is the recognition that business and IT leaders are no longer investing in huge upfront IT costs. Instead, they are moving to a cloud-delivered, subscription model.

Why? Cloud-delivered applications provide faster time-to-value for less cost than traditional enterprise software systems that have consistently failed to deliver the right information or functionality to the right people at the right time.

This executive paper introduces the concept of RBI and why this metric is fast becoming the new standard in assessing and benchmarking the value of your technology investment in the cloud. In particular, it examines the case for cloud analytics, which has huge disruptive potential to create rapid value in most companies while creating significant opportunities for better employee collaboration.

Cloud computing is challenging the on-premise traditional software markets at every turn, unleashing new price points, choice, accessibility and value delivered in ways as disruptive as the internet did 20 years ago. As an example, cloud analytics delivers The Power of 10:

  • 10 times more affordable
  • 10 times more value delivered
  • 10 times faster
  • 10 times more agile
  • 10 times more scalable
  • 10 times easier-to-use
  • 10 times more functionality

As an alternative to a $100,000+ analytic tool deployed over three months, the cloud option delivered as-a-service costs a tenth of that, and can be deployed in less than a day. The value of cloud computing can be proven before investment (RBI), initially on a small scale, before being scaled up as rapidly or as slowly as required. The impact on a company’s ability to accelerate innovation is unprecedented. 

A New Business Metric to Valuing Cloud Analytics

The problem with the traditional ROI model is that it solely measures the cost and return from on-premise investments over a relatively long period of time.

For some organisations, this is acceptable; but for many, having to wait more than six months for gains is increasingly difficult to justify to senior management.

Return-Before-Investment is used by companies to calculate not only the total cost of upgrading reporting systems by adopting cloud analytics, but to determine (using a data maturity model) where value will be created by whom within the company and when. It is quite common for organisations to realise significant value within days of subscribing to cloud analytics – well before any payment for the new platform has been made. This is even more the case where the cloud provider offers a free trial.

In summary, traditional ROI models show what you have to invest before you are even able to assess what value you might get out while Return-Before-Investment measures the benefits of what you get out immediately – before even paying for the first seat/license.

Return-Before-Investment captures the new economics of cloud computing; helping companies explain, rationalise and measure their adoption and usage of cloud-delivered applications such as analytics by:

  • Creating top-line growth through faster time-to-market for applications
  • Accelerating bottom-line cost savings through better utilisation of resources
  • Lowering the Total Cost of Ownership (TCO) of technology
  • Enabling organisations to focus on core business processes

But, cloud computing has done far more than just change how companies acquire and deploy technology. It has fundamentally altered the role of technology in companies by enabling employees to exploit data that has been to date inaccessible to them by facilitating collaboration more effectively than ever before.

Maximizing your investment in cloud computing, therefore, comes down to one thing: making the technology work for your employees, not vice versa.

The true value of cloud is greater than many realize – and it starts with RBI as the new barometer of success. Used smartly, cloud analytics is proven to deliver an initial payback immediately, inverting the traditional equation because there is zero deployment time and huge upfront cost with cloud computing.

Return-Before-Investment should be used by companies to compare on-demand services vs. on-premise solutions, before and during its deployment, to determine ways to continuously maximize investment in cloud analytics.

Cloud Computing Reframes the Economics of Analytics

Cloud analytics has enabled companies to create business opportunities by enabling knowledge workers to exploit the value of data in new and innovative ways without the upfront costs associated with on-premise investments.

But it’s not just a like for like cost. Traditional analytic architecture doesn’t support today’s knowledge worker – inhibiting the accelerated value creation measured by the new Return-Before-Investment model.

The objective of any analytics program is to ensure the delivery of the right data to the right people at the right time. Historically, this has been a huge cost for organisations because of the complexity of designing, deploying and maintaining on-premise solutions.

As you see in the diagram, 90% of the effort and investment in deploying and maintaining an enterprise-wide program resides with IT – and this percentage won’t decrease anytime soon because of the huge data volumes and number of sources companies are trying to manage.

Return-Before-Investment

This is not the case in the cloud because the delivery model provides companies with IT on-demand at a fraction of the cost of traditional business intelligence reporting systems.

To put this into perspective, cloud analytics delivered as-a-service offers more value for less. The cloud gives companies immediate, on-demand access to analytics without ever having to buy or build an analytic system or tool that involves integrating a data warehouse, ETL tools, servers, and much more into a seamless end-to-end process.

Three Steps to a Return-Before-Investment

  • Adopt universal app development: Companies that centrally aggregate data outperform industry peers because the data is widely accessible to business and IT teams. IT is able to effectively respond to and support the 24/7 demands of the business by collaboratively developing and sharing analytical apps in real-time from a single online app development and analytic platform.
  • Give employees self-service analytics: There is a difference between a reporting system and analytics. Unfortunately, many companies rely on reporting systems to make decisions when they actually should be using analytics, which facilitate the frictionless exploration, interpretation and collaboration of insight with minimal involvement from IT.
  • Bring in relevant information: Employees need context to make decisions so connecting your company’s internal enterprise data to information from external sources provides greater insight. For example, to mitigate disruptions to your supply chain, simply enrich supplier data with credit scores so you only do business with healthy companies. Call it big data or relevant data, it’s all about bringing context to decision-making.

 

 

 

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