How many steps did I walk today? How many clicks did this email receive? What’s the fastest route from A to B using public transport? These questions show how quickly we have become accustomed to analytics in our everyday lives.
Algorithms, embedded sensors and smarter data analysis enable us all to accurately measure our health, personal productivity and work performance. Companies have long known the value of collecting and analysing data to profile our buying behaviour and better predict what we’ll buy next.
Companies like Amazon and Facebook are using analytics to improve the buying cycle and their profit margins. There is still a way to go but these companies are using analytics to their advantage. In work, no department has been left untouched by analytics and business intelligence applications.
Marketing is well-versed in the benefits of analytics and its direct impact on company revenue. Sales is gathering insight into what business development strategies work the best. Finance is improving forecasting and return on investment measurement. IT is becoming increasingly efficient.
The language associated with analytics is also changing how we do our own jobs. Dashboards, real-time reporting, what-if scenarios, and predictive analysis have all entered our vernacular. We talk in KPIs. We look for outcomes in everything we do.
Underpinning this new digital workplace is a vast network of data centres. These immensely-sized buildings are the workhorses of the analytics world.
The figures associated with them are huge. Hyper-scale facilities use the same amount of energy as a small town. In the US alone, data centre 2014 power usage was the equivalent of 6.4 million average homes. This often leaves them under scrutiny, with companies having to prove and improve data centre performance to adhere to an organisation’s CSR promises.
Facilities cost billions of pounds to construct, manage and maintain. They are in a state of constant change, with new technologies changing the IT inside and customers demanding more and more data.
What is surprising and concerning is that the majority of data centres are still managed using outdated software and rudimentary data techniques. For example, many operational teams still use spreadsheets with potentially inaccurate data. This over-reliance on inaccurate metrics, baselines and manual calculations means organisations can struggle to accurately measure how facilities perform financially and operationally. In this day and age, that’s hardly an example of strong corporate strategy and leadership.
Analytics to the Rescue
So, when public perception and vast sums of capital are at stake, surely something needs to change? Some forward-thinking executives have begun to invoke the power of analytics to improve the forecasting, construction, management and analysis of facilities. And this analysis is also beneficial to companies investing in the data centre industry.
Predictive modelling software is being used to validate prospective data centre designs. This enables those responsible for site selection, construction and IT purchasing to precisely understand where the most economically viable location would be, and what equipment to use from an efficiency perspective.
Analytics also help accurately forecast the best type of facility for the business – be it a hybrid, cloud or colocation facility. Once constructed, real-time analytics tools let Finance better monitor the total cost of ownership of a facility.
If the business provides colocation or cloud services, the CFO can now conduct customer margin analysis - i.e. which customers generate the most revenue, are certain IT halls using too much power when compared to customer service level agreements? This data then filters through to operational teams who can better allocate capacity to maximise available resources.
The availability and performance of a facility is critical and being able to accurately predict both with analytics is revolutionary.
With these metrics, organisations can also provide concrete, verifiable data on the environmental impact of its data centre strategy. This data can provide answers to some of the most difficult CSR questions organisations are facing today.
The progress doesn’t stop there. Recent advancements in Machine Learning have made the business outcomes even more attainable, especially for professionals under pressure to provide quantifiable data on equipment lifecycle performance and the expected benefits from future investments.
Still unsure that analytics actually helps? Look at the use-cases.
Just this month, Google slashed its data centre energy bills by a massive 40 per cent using DeepMind, its Artificial Intelligence (AI) software. AI is improving data centre analytics by tracking patterns and continually cleansing data to provide the most accurate and credible data for future automated decision making. Companies are using similar analytics applications to reduce how much water their facilities consume - a massive boost to corporate social responsibility (CSR).
Businesses need to choose whether they want to be part of the problem, or whether they would prefer to be recognised for their leadership in business management, commercial positioning and environmental sustainability.
Put simply, Predictive Analytics, Machine Learning and AI technologies provide practical, immediate solutions to complex problems. This technology is no longer the future, it is in use by leading organisations today.
In the context of the data centre, this means the organisation receives clearer value on the financial impact, energy savings and CSR improvement of planned projects. Greater control is achieved. Finally, the business can guarantee the availability of other data-dependent business applications that rely on the data centre every day.
The next time you access any analytics dashboard, find out who within your organisation is responsible for the data centre that delivers the application. Ask them – are they using analytics themselves? After all, this might be your chance to recommend a solution that can generate impressive financial savings…
Richard Jenkins, SVP of Global Marketing at Romonet