How confident are you that your analytics initiative is delivering the value it’s supposed to?

These days, it’s the rare CEO who doesn’t know that businesses must become analytics-driven. Many business leaders have, to their credit, been charging ahead with bold investments in analytics resources and artificial intelligence (AI). Many CEOs have dedicated a lot of their own time to implementing analytics programs,

However, too many executives have assumed that because they’ve made such big moves, the main challenges to becoming analytics-driven are behind them. But frustrations are beginning to surface; it’s starting to dawn on executives that they’ve failed to convert their analytics pilots into scalable solutions.  It is clear from our own experience at IwP  that only a small fraction of the value that could be unlocked by advanced-analytics approaches has been unlocked

We’ve detected what we consider to be a number of alerts that signal whether an analytics program is in danger of failure. In our experience, business leaders who act on these alerts will dramatically improve their companies’ chances of success.

Alert 1.  Vision – The executive team doesn’t have a clear vision for its analytics programs. In our experience, this often stems from executives lacking a solid understanding of the difference between traditional analytics (that is, business intelligence and reporting) and advanced analytics (powerful predictive and prescriptive tools such as machine learning).

Alert 2.  Strategy – there’s no analytics strategy beyond a few pilot user cases. As with any major business initiative, analytics should have its own strategic direction.

We would suggest that there are three crucial questions the CEO’s must ask the company’s business leaders:

  • What threats do technologies such as AI and advanced analytics pose for the company?
  • What are the opportunities to use such technologies to improve existing businesses?
  • How can we use data and analytics to create new opportunities?

Alert 3. Analytics roles—present and future— are poorly defined. Few executives can describe in detail what analytics talent their organisations have, let alone where that talent is located, how it’s organised, and whether they have the right skills and titles.

Alert 4.  Translators –  the organisation lacks analytics translators. If there’s one analytics role that can do the most to start unlocking value, it is the analytics translator. This sometimes overlooked but critical role is best filled by someone on the business side who can help leaders identify high-impact analytics use cases and then “translate” the business needs to data scientists, data engineers, and other tech experts so they can build an actionable analytics solution. Translators are also expected to be actively involved in scaling the solution across the organisation and generating buy-in with business users. They possess a unique skill set to help them succeed in their role—a mix of business knowledge, general technical fluency, and project management excellence.

Alert 5. Data Cleansing –  costly data-cleansing efforts are started en masse. There’s a tendency for business leaders to think that all available data should be scrubbed clean before analytics initiatives can begin in earnest. Not so. We believe that companies may be squandering as much as 70 per cent of their data-cleansing efforts.

Alert 6. Analytics platforms aren’t built to purpose. Some companies know they need a modern architecture as a foundation for their digital transformations. A common mistake is thinking that legacy IT systems have to be integrated first.

Alert 7. Impact – nobody knows the quantitative impact that analytics is providing. It is surprising how many companies are spending significant sums on advanced analytics and other digital investments but are unable to attribute any bottom-line impact to these investments.

The companies that have learned how to do this typically create a performance management framework for their analytics initiatives. At a minimum, this calls for carefully developed metrics that track most directly to the initiatives. These might be second-order metrics instead of high-level profitability metrics.

Precisely aligning metrics in this manner gives companies the ability to alter course if required, moving resources from unsuccessful use cases to others that are delivering value.

 In summary, there is no time to waste. It is imperative that businesses get analytics right. The upside is too significant for it to be discretionary. Many companies, caught up in the hype, have rushed headlong into initiatives that have cost significant amounts of money and time and returned very little.

By identifying and addressing the failure alerts presented here,  companies have a second opportunity to get back on track.

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