Analytics continues to be one of the growing categories of software expenditure as it has for most of this decade. Much of this expenditure has been on standalone analytics which can give great insights but not necessarily change the underlying performance of enterprises.
One reason for this is that analytics by itself does nothing. Knowing facts does not mean that you can act on them. Unless users can combine better decision making with better execution of such decisions it is a waste of money.
Before developers spec new analytics functionality they should check what decisions need to be made and what action will be taken as a result of those decisions.
That means that all staff and stakeholders across an organisation that need analytics should have full access. Not only that but also the ability to customise according to changing priorities and the key tasks they are currently engaged in.
Then there are team leaders, project managers and executives that need different answers. They need to be able to query data and create new dashboards and reports without having to go back to IT. That is where self-service BI and analytics come in as long as you don't have to be a fully fledged analyst or data scientist to cope!
There is still another group, maybe a minority but an important minority. These are business analysts that need to discover data, draw new insights and share these with colleagues who wish to transform the business.
And do you want to just present great insights or do you wish to execute better decisions? If the latter you will want to have a "bi-directional BI technology" able to write-back to web services, reporting databases, feedback loops. This is critical, for example, in insurance company claims processing.
What often happens is that different products are used for the different use cases; Qlik and Tableau or Spotfire for analysts for example . Far better and secure however is to chose a platform that delivers relevant analytics to all three categories of users I have described.
The questions that Charles Caldwell poses are very important to ask. Then you will end up with the right technology, right vendor and right solution
Great! You’ve decided to invest in an embedded analytics solution. Now what? How do you ensure that you select the right solution to provide the capabilities you need. Picking the right solution involves thoroughly evaluating the technology, understanding the expertise offered by the vendor, and implementing a process to ensure success. Evaluation Criteria The first step is to examine the evaluation criteria that are critical to embedded analytics implementations. Below I’ve outlined both the technical and non-technical requirements that are common to most evaluations, which you should consider
