We help you create a clear data narrative for your business, along with a roadmap to guide your transformation. Here’s some of the typical customer challenges and opportunities we see.
DataStrategy - Element - Competitors
Our competitors are increasingly investing in data. We know we should do the same, we’re just not sure where to start.
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DataStrategy - Element - Buzzwords
How should we react to the latest data buzzwords and trends? Do we need to ‘do’ AI and machine learning?
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DataStrategy - Element - Invest
We’ve invested heavily in data and technology - but no one seems to be using it.
False
DataStrategy - Element - Acquisition
We’ve been through a range of acquisitions and need to unify our strategies and ways of working.
False
DataStrategy - Element - Innovation
We can get ahead of our competition by investing in data early, using it to steer innovation and operating efficiency.
False
DataStrategy - Element - Connect
We understand data but it could do more for us: we don’t connect it well with our business strategy.
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DataStrategy - Element - Customer
We need to know what a ‘good’ customer looks like – and what a ‘great’ customer looks like.
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DataStrategy - Element - Products
We want to get better at using data to develop new products and services.
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Diagram_Our resources and capability - DataStrategy
Our approach to data strategy.
Linking and prioritising data initiatives against your business objectives.
Working closely with your business stakeholders, we design actionable data strategies that shape and guide your investments. We map data initiatives to business objectives - first identifying the data opportunity, then creating an over-arching data vision connected to business ambitions.
We take the time to understand what makes your organisation different, the challenges and opportunities you face, drivers for change in your industry and the evolving competitor landscape.
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DataStrategy - Maturity Assessment
DataStrategy - Maturity Assessment
Maturity assessment.
We then analyse your existing data maturity against our proprietary benchmarking tools and agree a target state to deliver on your data potential. As part of this, we collaboratively scope initiatives designed to accelerate maturity in a balanced way.
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Data Strategy ValueProp-Roadmap
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DataStrategy - Roadmap
Roadmap.
Using ideation and planning frameworks, we then create a roadmap to steer your data transformation, identifying a series of early initiatives to deliver rapid value and build momentum around the path to data-driven success.
We work with you to specify a set of initial data projects at a sufficient level of detail to create an actionable first step. We also help you create a high level investment case to accelerate internal sign off processes and socialise plans for leadership buy-in.
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What it means to you table - DataStrategy
How we work and what it means to you.
How it work & what it means to you.
How we work.
What it means to you.
Definition of a clear narrative around the role of data in your organisation’s future.
Align your teams around a single vision for data and its relationship with your key business goals and objectives. Help stakeholders understand the potential and their role in driving data maturity.
Research & analysis: what your competitors are doing with data and the pace of change in your industry.
Understand drivers for change in your industry and the evolving competitor landscape. Take inspiration from success stories and avoid pitfalls. Create momentum.
As-is and to-be state definition.
Visualise the gap between current and future capability to support and drive investment cases, enrolling senior leadership in the journey.
Roadmap to target state, developed in collaboration with your internal programme leadership.
A clear view of the the primary work to be undertaken, the inter-dependencies of initiatives and activities and a well-specified set of recommended immediate first steps. A cohesive roadmap of workstreams and initiatives gives you a practical route to balanced data maturity build out.
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IN ACTION
DATA - DataStrat CaseStudy
GAP Group
Unlocking the power of data and analytics to accelerate growth.
Established in 1969, GAP Hire Solutions is the UK’s leading independent equipment hire company. With ten divisions and over 140 locations across the UK, they provide everything from diggers and tools to track mats and portable toilets.
GAP Group were looking for an experienced partner to design an effective, practical roadmap designed to build strong links between data value and business objectives. Our data consultants explored and analysed GAP Group’s business and competitive landscape to understand the opportunity for data-driven innovation. We collaboratively developed a set of candidate data projects linked to key domains like Informed Business, Better Consumer Conversations and Intelligent Decision-Making, delivering a data strategy and roadmap of initiatives for delivery over the next 2 years.
Logo- Data - Case Study - DataStrategy Services
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Our customers.
We love what we do and we get to work with some of the sharpest minds in the brightest businesses: from smart home devices, space exploration and beer to manufacturing, finance, ecology and logistics.
Creating compelling omnichannel experiences from bar to browser.
BREWDOG
Optimising performance & support with 360° insight into the elite Women’s game.
ENGLAND & WALES CRICKET BOARD
Democratising data to engage new communities & protect the UK seabed.
THE CROWN ESTATE
Delivering the horizontal scale to expand into new medical research fields.
HANSON WADE
Improving experience & making life simpler for home automation customers.
HIVE
Bringing on-demand to the UK’s favourite TV listing and review platform.
RADIO TIMES
Reducing cost, accelerating innovation and attracting new talent in healthcare.
Our Chief Data Scientist, Rich Pugh, on data within successful digital transformation.
Digital Transformation
2022-11-04T22:00:00Z
Watch & listen - 5 November 2022
Digital Transformation
Data Science
Data Transformation
The 5 pillars of data transformation.
Insight
Organisations on a data-driven journey want to achieve value from their data. Download this whitepaper to learn how to get started on your data-driven journey, and discover the pillars that define a successful transformation.
Organisations on a data-driven journey want to achieve value from their data, but what they are attempting isn’t really about digital, first and foremost — It’s actually about the necessity of transforming business models.
Download this whitepaper to learn how to get started on your data-driven journey, and discover the pillars that define a successful transformation.
Do you know who owns the data in your organisation? Should you care?
Blog
Branka Subotic, Ascent’s Principal Data Consultant looks at the various data roles within an organisation and the business-wide responsibility to make data-led business decisions.
data ownership, data owner, data steward, technical strategy, data & analytics, data-driven, data custodian
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2021-12-12T00:00:00Z
Do you know who owns the data in your organisation? Should you care?
Data is arguably the biggest asset an organisation owns - but who’s ultimately responsible for it? Ascent’s Principal Data Consultant Branka Subotic considers the roles and responsibilities of data ownership.
Have you ever sat in a meeting with your Board or executive team when a really obvious question was asked that nobody truly had an answer for? Do you recall an uncomfortable silence followed by a senior leader providing a half-baked response (whilst two other senior leaders frantically messaged their teams)?
If you do (and you are not in the minority!) - ask yourself this: who should have had the answer? Who owns data in your organisation?
Data should drive ALL business-critical decisions.
The Covid-19 pandemic has disrupted (and is still disrupting) most industries. For some, it has led to a complete standstill for few months, and an urgent need to re-finance and cut costs. For others, it has meant a boost in sales and unprecedented growth.
Regardless of where your business stands in between these two extremes, you can say that it has taught us all how important it is to have accurate, readily available data that informs critical business decisions. Often, this is data which describes productivity per location, per sector, per type of product, per team, per employee, or it simply indicates the actual number of products sold, customers engaged, or employees in the company.
Let’s run with the latter example. If you ask HR how many employees there are, you will get a figure including everyone who has a contract with the company, permanent staff as well as contractors, but also staff who are on unpaid leave, special leave, sabbatical, secondment, etc.
If you ask Finance, you will get a number that reflects staff on the payroll. Therefore, the answers to the same question from HR and Finance will be different – but both can be considered ‘correct’. But which answer should you use to drive your business?
Governance and trust: data roles.
Data and analytics assets exist everywhere across an enterprise and vary in nature – and not all data and information is equal. Gartner suggests establishing a trust-based governance model that:
supports a distributed ecosystem of data and analytics assets
acknowledges the different lineage and curation of these assets, and
assists business leaders in making contextually relevant decisions with greater confidence.
The last point above is key - it all comes down to context. If we consider our earlier example, the scenario might be that the CEO is asking how many employees the company has because they need to decide how many they will furlough. Providing this kind of answer is only possible if the ‘People’ data in this company has a single owner who has a framework in place to steward the relevant data sets and deliver context-specific, relevant answers to organisational questions.
Which brings us to data governance roles. There are various approaches to the delineation of responsibilities around data but one of the simplest (and therefore my favourite), is the distinction between Data Owner, Data Steward and Data Custodian. You can read vast amounts of material on each of these roles from either Gartner or DAMA, but, succinctly, this is what they mean to me:
A Data Owner is the person accountable for the specific and logical groups of data assets (in our example, all data sets that constitute ‘People’ data), whether generated by the company or 3rd party (e.g., postcode database). The Data Owner can be a member of the executive team or a senior manager with delegated authority and a vested interest in ensuring data is managed appropriately.
A Data Steward is responsible for maintaining specialist knowledge about their data area, putting into place acceptable use of this data, maintaining necessary records about the data (metadata) and is consulted for operational advice regarding any changes about the acquisition, transformation, storage and consumption of this data (where consumption includes both human and system usage). They implement data strategy enterprise-wide for their data area and are also responsible for performing any transformations required for their data assets.
A Data Custodian is responsible for a set of data. Data Custodians are essentially data administrators who focus on the ‘how’, rather than the ‘why’ of data management. Data Custodians must communicate and collaborate with the Data Steward regarding any technical activities that impact the data within the Data Steward’s scope.
Here’s how that looks in practice:
Data governance ensures that the right people are assigned the right data responsibilities. It is mostly about strategy, roles, organisation and policies, whilst data stewardship is all about the execution and operationalisation of said policies for the benefit of the whole business, making sure that the data is accurate, in control, and easy to discover and process by the relevant parties.
NB: It is very important we do not mix Data Stewardship in any way with the business function within which the Data Steward happens to sit. The role they perform is company-wide.
In our previous example, the Data Steward for the ‘People’ data may well sit in the HR department, but they are responsible for the single source of truth for a total number of employees, staff demographics, contact details, licences/ qualifications and their validity, etc. Similarly, the Data Steward for the ‘Customer’ data could easily sit in the Commercial department, but their remit is to manage a complete and accurate set of customer data for the whole of the business.
“So what?”, you say. Why should you care about all of this?
It all comes down to a single source of truth. When your Executive asks a question, you want to make sure there is a single party responsible for getting to the answer, using a managed, quality-checked data source or sources. You want to prevent different parties going off on a tangent trying to answer the same question in silos, using locally produced data sets that are not quality checked, resulting in different answers, delivered in different formats with a range of differing assumptions.
What is good is to start asking this question today (not next week, or the week after). The longer you let the business evolve without a clear answer to who the data owners are, the longer you will lack clarity about your business, its performance, and clear lines of accountability.
So see your data for the asset that it is: go ahead, be brave, ask the question. And if you need a hand, the Ascent team is here to help you every step of the way!
Branka Subotic
Principal Data Consultant
Ascent
A strategic thinker, Branka is passionate about data, specialising in strategy and transformation. Branka’s primary role at Ascent is to help customers turn data into insight to support operational decision-making, having established her credentials in a mission-critical context: leading key alliances and advanced analytic teams in European air traffic management for over 15 years.
Branka is also a Chartered Engineer with a PhD in air traffic management, an MSc in aeronautical science and an MEng in air transport engineering.