Integrate the wide range of data streams we identified so that our client could understand stakeholder relationships and their causes.
● Align program initiatives with corporate strategic objectives to indicate impact and assist with strategic planning and efficacy analysis.
The engagement reinforced my belief that successful implementation of data analytics involves various departments and functional areas of the modern enterprise working in close collaboration. It includes departments like IT, communications, operations, human resources; functions like data science and business strategy; and subject matter experts.
The key word is collaboration. Experience shows that the total is always more than the sum of its parts.
Addressing reputational challenges successfully requires:
● Building a framework to enable reputation to be used as a strategic advantage with customers, governments, partners, and employees.
● Monitoring, evaluating, analyzing, and responding appropriately in real time.
● Predicting where and how communications will have an effect on reputation (for example, crisis life cycle, regression analysis).
● Learning how to allocate resources appropriately to gain maximum Reputation Strategy advantage.
While it is possible to outsource certain components of Reputation Strategy, companies should also consider developing their own internal expertise and experience.
Reputation Is Not a Momentary Phenomenon
Reputation building is a long-term strategic endeavor. It is an integrated set of ongoing processes, not an individual program, campaign, or one-shot initiative.
Moreover, reputation is not a singular event or state. Reputation has multiple states and forms. It changes over time – sometimes slowly, sometimes with breathtaking speed. Building a reputation that is strong, resilient, and not fragile requires top down leadership, executive sponsorship, and buy-in at all levels of the enterprise. It requires written policies, training, incentives, and discipline. The concept of reputation as a strategy must be woven into the culture of the organization.
In great, progressive companies, reputation is an integral part of the cultural DNA. It isn’t an afterthought; it’s top of mind.
Don’t Try This at Home
Because Reputation Strategy is core to a company’s operations, with complex requirements for data, processes, and people, this transformation should not be thought of as a “do it yourself ” or “back of the envelope” affair. Smart organizations will set aside the time and devote the resources necessary for creating and sustaining practical reputation strategies.
Reputation Strategy is a set of scientific multidisciplinary processes that must be integrated into business planning and embedded into operations across business units and geographies, with the proper executive sponsorship. Ultimately, accountability sits at the highest level of the organization. The CEO and the board must drive awareness of the strategy and keep employees at all levels engaged.
Net Takeaway
In a transparent world, reputation is a strategic asset and core competency requiring a blend of communications analytics, data science, and multidisciplinary expertise. It should be treated as a competitive business advantage.
Reputation Strategy provides tangible value to organizations through:
● Creating trust in the organization’s products and services
● Providing access to policy and decision makers
● Attracting and retaining the best employees
● Driving credibility with outside partners
● Serving as a critical success factor for investors
Reputation must be protected and enhanced through authentic organizational values, decisions, behaviors, and actions. It requires a clear and evidence-based Reputation Strategy, based on a carefully orchestrated portfolio of analytics that illuminates consumer attitudes and creates predictive models that anticipate consumer behavior.
Chapter One
Welcome to the Networked Ecosystem
Executive Summary: In a digital networked ecosystem with no clear time or physical boundaries, traditional strategies and tactics deployed by communication professionals will not work, and might even be harmful. Newer and more agile methods based on careful data analysis and scientific reasoning are required.
These days, it seems as though every executive feels obligated to talk about the critical need for collecting data, managing data, analyzing data, storing data, and harvesting insights from data. All of those activities are important, but what’s even more important is creating a corporate culture in which data is respected, valued, and understood. From my perspective, the primary barrier to extracting value from data is culture, not technology.
The processes of data science are inherently collaborative and cross-disciplinary, which essentially means you cannot do data science in a vacuum. It cannot be relegated to the basement or to a back room. It’s a team sport. There are plenty of moving parts that require careful orchestration and dedicated leadership.
Too often I see data siloed in specialized groups or I hear people talking about using data to generate insights. Your organization can have all the insights in the world, but they will not help unless you have a culture that knows how to transform those insights into ideas and effective decisions.
In the twenty-first-century economy, data is the fuel we use to make better decisions. It’s the raw material from which we manufacture success. We have to use that data and then take action.
Changing the Culture
Saying that an organization is “data driven” doesn’t mean it’s being run by computers. It means that key decisions are informed and influenced by evidence, which is derived from data. Not every decision needs to be made by human beings – an increasing number of decisions can be delegated to software applications and other forms of automation. For example, you don’t need a human to decide whether to turn on the air conditioning in the summer. That kind of decision can and should be automated.
For the most part, we’re fine with delegating straightforward decisions to machines. But now there’s a widening area in which we’re not so sure how much decision-making power we really want to share with our software applications. For example, farmers used to decide when to water their crops. Now, exquisitely complex systems of machinery, software, mobile devices, and sensors – including cameras mounted on airborne drones and orbiting satellites – decide when it’s necessary to turn on the spigot.
The real question facing us is whether we want to use our increasingly sophisticated decision-making technology not just to grow better grapes and keep our shopping malls cool in the summer, but to improve the performance of our companies and organizations.
The question that executives should be asking is not about technology. For the most part, the technology you need to make better decisions is already available. The question executives need to ask is this: How do we transform our organizations into data-driven cultures?
The Digital Revolution Has Rewritten the Rules
It’s not exactly fresh news that digital information technologies have changed everything, but it’s worth repeating: Digital information technologies have changed everything.
On many levels, we all understand that we’re living through a revolution, but the reality has not fully set in. In the communications industry, for example, most of us pay lip service to “new media,” but few of us are genuinely comfortable operating within the digital environment, which now surrounds and envelops us so completely.
Some of my best friends still pine for “the good old days” when most of our business was done at lunches or over the phone. I also experience a twinge of nostalgia and fondness for the past. It’s only natural. In the past, everything