Regular cost and data analysis
The cost of storing increasingly large data volumes is becoming unrealistic, so much so that a recent IDC report reveals that 87 percent of companies are keen to reduce storage costs. However, many organisations appear to lack the commitment to effectively reduce cost, whereas even at the proof of concept stage, many MSPs promise to deliver cost reduction. As a result, the anticipation of cost reduction becomes a driving force in any partnership between an enterprise and an MSP. This, in turn, leads to cost becoming the primary reason for the implementation.
This motivation to reduce costs and MSPs' typically eagle-eyed focus on budgets enable them to deliver massive cost savings. An MSP may be able to help companies slash costs, boost staff productivity and accelerate time-to-revenue in the process.
An enterprise's IT department must redefine its role within the business as a profitable IT bureau to the various divisions, which raises the controversial concept of departmental billing for these divisions within an enterprise. This encourages better visibility, in terms of cost and utilisation of storage space, by each business division or function, while ensuring that departments are made accountable for their consumption of data services.
Additionally, good MSPs recognise that the value of data is subject to change, for instance, the 'gold' category of data today may drop in 'value' depending on factors, such as creation date.
It is therefore, essential that data must be evaluated regularly to ensure that the storage tier warrants the value of the data. Expensive disk space might have once been warranted for data which need to be stored for compliance purposes. However, it might not justifiable at the same tier following expiration of the legally dictated timeframe. Crucially, limited IT budgets do not support business needs adequately. Therefore, reducing data management costs with a more efficient data infrastructure will free up budgets—enabling companies to pursue opportunities that can power business growth.
Automation is key
Data management is a complicated business, and it is becoming increasingly so. When making storage decisions around corporate data, organisations require a degree of foresight, in terms of what they expect from their data environments. Data growth, for example, is something that is unavoidable. An IDC survey reveals that Singapore-based enterprises are actually twice as likely as the average Asia Pacific organisation to anticipate year-on-year data growth of more than 51 percent. This leads even more enterprises to leverage on public cloud for 'pay as you grow' models, preventing budgets from being locked up in under-utilised hardware.
In addition to being scalable, data storage platforms must offer some degree of flexibility. In the retail industry for example, data levels fluctuate. We have seen that there are certain times in a month or year, where retailers' data levels rise significantly, only to fall drastically, where they could remain until the next 'peak' period. In these cases, if an enterprise is to run an efficient data management system, the cloud model that the enterprise opts for must offer some degree of flexibility, as well as scalability.
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