Connecting

Experience

Creating benefit for our clients by reducing costs and generating competitive advantage.


Clarity through Data Strategy.

A data strategy linked to your business strategy is critical to ROI from data investments.

A data strategy needs to sit at the heart of your business strategy. The data strategy ensures that your organisation truly thinks of and manages data as a strategic asset.

The data strategy outlines your organisation’s vision for managing data as an asset and leveraging data for competitive advantage. A 360º view of your customers, suppliers, competitors and operating environment enables you to plan and react ahead of time.

Companies we have worked with who had previously failed in their digital transformation journey consistently lacked a comprehensive data strategy linked to their business strategy. We found this often led to vague or unachievable KPIs and delivered insights based on untrusted data or one-off self-service visualisations, which could not be relied upon.

Having a data strategy, on the other hand, is key to delivering ROI from data programmes. For example, Parity Experts were able to save a global manufacturing company millions of pounds by defining a Strategic Knowledge Model and implementing Business Intelligence around that governed and trusted data model.


Optimising Operations and Outcomes by Orchestrating Data.

Organisational changes to ensure data captured is reliable, consistent and identifiable are vital before data can be used to create meaningful insight.

Integrating data into a single governed source, using automated processes, is key to optimising operations and achieving desired outcomes.

We have found a raft of underlying reasons for organisations’ failure to achieve desired outcomes. These included lack of a Strategic Knowledge Model, ungoverned data sets, weak change management process, not leveraging ETL tools to their full potential, creating non-optimal operations and custom extracts, and spending too much time and resources actioning data movements in and out of repositories and tools, rather than analysing data.

We have experience in developing and implementing corporate Data Standard Strategies to enable data optimisation. Through this work our clients have obtained benefits in:
  • Supply Chain Optimisation: fulfilment of raw materials to factories (cross borders) from geographically dispersed warehouses rather than a local warehouse. This could only be achieved through use of governed transformed unified data sets.
  • Improved data science analytical services leading to quicker and better quality insights
  • Automation of and improvements to ETL processes and integration to single source of truth repositories


Building Trust and Robustness on a Firm Data Platform.

The right data platform is key to deriving value from data.

Having the correct data architecture in place underpins a robust data platform and provides the right data in the right format for your analytical services. This architecture needs to be planned and implemented.

Customers often come to us having previously taken a reactive approach, jumping to conclusions that a big data or columnar store platform would be the cure for their ills. They act without a proper plan for their data platform, often blindly following industry trends or migrating for migration’s sake.

Parity has experience in the design and implementation of extensible data architecture and maximising use of clients’ existing platforms. We have built data warehouses and data marts for our customers including a generic, configurable, meta-data driven warehouse. We have provided tuning and optimisation services on terabyte size databases providing 24×7 availability.


Generating Competitive Advantage by Closing the Gap from Information to Insight.

The importance of choosing the right tools to generate insight from your data from a vast range of options.

The vast array of available technologies to gain insight from data leads to confusing and difficult choices for businesses.

We find that companies with a self-service approach found that early insights and predictions were quick to produce and seemed of good quality; however, the insight quality or the predictive model quickly became untrustworthy. Companies using an IT-provided and supported solution fared better; however, their solution was often slow to adapt to business needs and they were constrained by lack of data science resources.

Our customers gained competitive advantages from our work in the appliance of Data Science and advanced SQL analytical services in the systems we have developed such as:
  • Strategic scenario-modelling and resource-optimisation systems
  • Integer-allocation algorithms for modelling allocation of thousands of trained staff to posts
  • Advanced semantic parsing engine to decode manual and automatically encoded messages
  • Configurable scenario-modelling application for investigating the optimal allocation of overheads, from cost-centres to profit-centres
  • Property Asset portfolio of 50,000 assets; the models provided optimal life-cycle programmes covering condition, repairs, refurbishments, maximised rental income and disposals


Reducing Risk by Modelling Military Capability.

Be less at risk of unfunded liability and more able to plan effectively for changes in policy and operational necessity
When the built-up (and through-life) cost of delivering a given outcome is not known, then how can an enterprise understand the consequences of cuts to their budgets (on those outcomes)? Equally, what if the required outcomes are changed, due to necessity or changes in policy?

Why is it important for private-sector enterprises to clearly understand the relationship between overheads and delivery functions? There are obviously many reasons but there are two particular drivers:
  1. Having a clear model of the relationships allows them to calculate the profitability of delivery units and the products they may make and sell, for example;
  2. It also allows profit-making businesses to offset the expenditure on overheads against their tax-liability, allowing them to pay less tax.
Any business which does not have a clear model of their overheads and how they can be aligned to delivery and profit is in significant need of one. What about enterprises that do not pay corporation tax or do not generate revenue, meaning that there can be no need to consider profit? Would they have invested the time and effort required to understand these complex relationships? Understandably, probably they would not; but there is a very good reason they ought to.

Parity has extensive experience in understanding and modelling the built-up costs of both private and public sector organisations, and their relationships to outcomes.
The Parity Capability Costing method allows us to build you a deterministic model of your enterprise, which you can use to understand your organisation and model the effects of possible or real changes.