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The changing face of data analytics – from data models to future proofing


The changing face of data analytics – from data models to future proofing


Every business today has more data and information than ever before. We all have mountains of sales data, media data, website data, social network data, pricing data, digital data and survey data on our customers and competitors.

The challenge is how and what to you do with this massive amount of information? The problem is we all know too much. We are data heavy but light on real insights.

It is one thing to understand buying trends and forecast demand for a particular product. It is another to then be able to use this strategically and tactically to identify behavioral patterns, plan campaigns and even help a business develop new products based on the insights.

Enter the world of analytics  – where this data stream can be become real knowledge to give ourselves an advantage in an ever more competitive market.

The real value to businesses worldwide today is not just the ability to report on what happened, it is the ability to help predict what will happen and to translate mountains of data into significant and targeted business insights and outcomes that contribute to a company’s bottom line.

Traditional analytics has not helped its role in organizations by shaping these data streams into more data streams, creating models and frameworks that perform high end statistical calculations without generating much value. A lot of the time, they tell us how the business is or was performing. The new frontier of analytics can tell you what tomorrow will look like.

Consultants should be focused on creating greater future value out of their current data. We can do this by helping them interpret their data and translate it into practical applications. It's about putting the right information into the hands of the right people at the right time.

The solution is not more data

A common mistake we see many marketers make is to look to collect more data in the belief it will help solve their problems.

Our start point is to look at what data is needed and if it exists. Only if we are missing data that would shed light on a business issue would we go out and collect more data.

The technology used to analyze data today is readily available, but in many cases very difficult to activate successfully within businesses. Why is this?  It is because the traditional analytics roles within many firms are there to produce numbers and not business outcomes.

The hard task is getting the people who understand the complexity of the analytics, but can work with senior managers so that they understand the outcomes to make decisions. No one likes the black box model and nor should they.  A focus on technology can easily distract you from the real aim which is a better view of your customer.

Do you need to change your business culture?

Where many companies fall down is leveraging data and how strategically they can integrate it into the decisions made in an organisation based on that data.

It is one thing to have improved analytics and reporting tools but unless they are shared widely inside your business they are likely to have little effect on strategy and success.

A key issue we see, and one many marketers overlook, is the fact that a cultural change needs to take place within their organisation. This is needed if they are to fully exploit the value hidden in their customer data.

Rather than try to simplify all data threads into one huge “dashboard” with static metrics, companies need to be able to dip into this to provide multiple views of the business when and where they require. Businesses are dynamic and the analytics required are also dynamic.

It is interesting when we talk to clients how frustrated they are in this area. A client in the financial services sector told us that they “had everything” in terms of data. They were not wrong. The issue was bringing it together in such a way that the connections and interplay were visible to the business and as a consequence more effective decision making could take place. The links and connections are what we believe make data powerful – not the streams in their own right.


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