Making better business decisions is easier thanks to the availability of so much more information. But making those decisions fast – especially when that information has to be culled from disparate sources and often shared with colleagues – is still a significant challenge for many enterprises.

Certainly new advances in business analytics have enabled a tipping point to speed insight, decisions, and action. But for companies that rely on systems of record – those that merely process transactions and store data – performance improvements aren’t so easy to achieve. To move the performance dial, these companies need to investigate the evolution toward systems of engagement that enable business users to access, analyze, share, and discuss information as well as make decision in a single environment. And more often than, fast.

To remain competitive, companies must accelerate their ability to analyze data and make decisions in real time. The Internet and social media tools, in particular, are turning transactions into “if-you-snooze-you-lose” scenarios. In digitally mediated environments, companies have much smaller windows to address and modify transactions to make them more productive and profitable.

The growing appreciation of collaboration as a decision enabler is another game-changing trend. Decision-making nirvana is closer-at-hand when systems help business users collaborate internally, with customers, or with suppliers to make the right decisions at critical moments of engagement.

The good news is that technology companies are well aware of their customers’ need for better, faster, collaborative data analysis. On the inter-enterprise front, technology companies are coming to market with a variety of next generation communication and collaboration tools.

Equally important, more transparent interfaces between current systems of records are evolving into systems of engagements. These tools provide end users the ability to access, analyze, share, and discuss information and make decisions quickly, all in a single environment.

Leveraging networks of people via social media mechanisms is a vital component of this engagement model – especially when the unstructured data they provide is often what’s necessary to make a decision.

In a report from TCG Advisors called Speeding Insight, Decisions, and Action at Critical Moments of Engagement: Boosting Performance Through Business Analytics authors Philip Lay and Geoffrey Moore suggest that companies take a fresh look at data analysis, but do not act impulsively. “The impact of putting business analytics more directly in service to business users may be revolutionary,” write the authors.  But “the deployment of these capabilities atop established systems of record must necessarily by evolutionary.”

Related systems are simply too massive and entrenched to be managed in any other way. And while some teams within an enterprise may have a high level of analytical maturity, the rest of the organization may not have the skills or resources to collaborate in a meaningful way.

So what’s the Darwinian thing to do? Lay and Moore suggest that CIO’s begin by addressing the critical moments of engagements that have the most immediate value and impact on the business. The best way to win credibility with business users and provide with real, immediate short and long-term value is to give them the information they need at the critical moments of engagement.

In the process, CIOs should focus more energy on empowering the middle of the corporate hierarchy, as opposed to the front-line transaction workers at the edge or the executive teams at the time. Give precedence to enabling teams to collaborate on “social” data to determine next steps over the more pristine single-source-of-truth based decisions that drive longer-term strategies.

Six Stages to Making Better Decisions

A data analysis model that supports decision making at a variety of critical moments of engagement doesn’t look very different from traditional processes. But its structure is not really a maturity model of linear steps. Instead, organizations should be able to address the stages of decision making in any order.

Authors Philip Lay and Geoffrey Moore prioritized stages in the following order, but emphasized that steps 3 and 4, are at the epicenter of the evolution from business intelligence to business analytics. At those steps, systems of engagement meet systems of record to enhance the productivity of business users making decisions in real time.

1. What happened? Identify a critical moment anytime, anywhere, on any device – while still maintaining the necessary security protocol.  Reports must be accessible at all levels of the organization.
2. How and why did it happen? Move seamlessly from triage to effective communication between data analysts and business users to ensure analytics map accurately to real-world events.
3. What is happening now? Deliver concise reports to the organization in context and in real time. Integrate those crucial communications into the systems of engagement that will be deployed.
4. What is the next best action? Make core recommendations that are key to engaging online users. B2B situations require more expert recommendations as opposed to closed-loop actions – made hugely more valuable by virtue of exposing them to the critique of interested parties via a collaborative infrastructure.
5. What will happen? This is a domain of extrapolation where the focus is on trend detection as an advanced alert – imperative for high-volume processes at the heart of social services and viral marketing.
6. What are the best-case and worse-case scenarios? Analytics can bridge the quantitative and qualitative, crucial for long lead-time sectors like energy, transportation, and public services.

Read more about the 6 steps to better, faster decisions (no registration required).