How about trying complex Data Analytics Solutions for size and fit, before you splash the cash?

by Alexander Heidl - Analytics & Business Value Consultant, Teradata International

The pressure to deliver Alpha – potential above the market average – is immense. And that’s not surprising because in a quick-change disruptive world, Alpha consistency puts an organisation at the sharp edge of its digitally-driven market. If it can be done quickly, that is.

One of the biggest stumbling blocks to creating breakthrough insights that drive value though, has been the time it takes to realise or monetise the business potential in data. But what if I said that instead of waiting months or even years for project results you could deliver Alpha, fully, within 6-10 weeks?

And what if I told you we could predict the business value of analytic solutions before you shell out a ton of money on the technology and other resources?

What would that be worth to your organisation? To you, personally?

The RACE for business value in data

Predicting outcomes is complicated. A myriad of different things that complicate the deployment and business use of analytic solutions need to be taken into consideration, like new data sources (including IoT sensor data) and new analytic techniques, for instance. Yet, in spite of this giant basket of variables, the potential ROI and strategic business impact of any analytic solution is expected to be totted-up and delivered to the table before any money changes hands.

Which is where Teradata’s RACE approach comes in. Teradata’s agile, technology-agnostic process, RACE (Rapid Analytic Consulting Engagement), has been developed to complement both agile development (e.g. CRISP) and agile methodology (e.g. SCRUM).

Crossing the Business – IT divide

The RACE process also soothes a number of old wounds. Business departments pass their needs and ideas onto their analysts, who simply respond. And, whereas IT departments have their processes, business and their analysts don’t really have a way of streamlining business value identification before hitting IT with a development request.

Often (surprise, surprise), business departments don’t understand the analytical potential of data. At the same time, neither the analysts nor the IT department understand business processes and ideas. Consequently, business thinks IT is too slow; IT feel they are not taken seriously and have no clue about how the business is really run.

One of the great things about RACE is that it fuses business and IT together through its leadership and commitment model. At the same time it enables both sides to intensively learn from another.

It’s a three-phase approach

RACEing involves three primary phases:

  1. Align – together, business and IT identify and align the highest-potential-value uses cases, and validate the availability of key data assets to support the use case.
  2. Create – data scientists load and prepare the data developing new, or applying existing, analytic models to the selected use cases. This phase involves rapid iterations with the business to ensure the analytic insights hit the right business targets.
  3. Evaluate – business and the analysts / data scientists analyse the results and document the potential ROI of deploying the analytic use cases at scale, as well as developing a deployment recommendation.

RACE leverages multi-genre analytics to generate new business insights, reducing time to market (takes average of 6 weeks to validate ROI in the new business insights), and minimising deployment risk (generated insights act as a prototype for operationalisation). Oh yes, it identifies the Alpha by validating use-case business potential, too.

And the upshot is that you begin each project with a clear ROI roadmap which answers three burning business questions: “How?”, “Where?”, and “What will it be worth?”

What’s not to like?

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